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GetFreeCourses Co-Udemy-The Data Science Course 2022 Complete Data Science Bootcamp
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01 - Part 1_ Introduction (Size: 7.79 GB) (Files: 1417)
01 - Part 1_ Introduction
001 A Practical Example_ What You Will Learn in This Course.mp4
001 A Practical Example_ What You Will Learn in This Course__en.srt
002 What Does the Course Cover.mp4
002 What Does the Course Cover__en.srt
003 Download All Resources and Important FAQ.html
16507136-FAQ-The-Data-Science-Course.pdf
external-assets-links.txt
02 - The Field of Data Science - The Various Data Science Disciplines
001 Data Science and Business Buzzwords_ Why are there so Many_.mp4
001 Data Science and Business Buzzwords_ Why are there so Many___en.srt
002 What is the difference between Analysis and Analytics.mp4
002 What is the difference between Analysis and Analytics__en.srt
003 Business Analytics, Data Analytics, and Data Science_ An Introduction.mp4
003 Business Analytics, Data Analytics, and Data Science_ An Introduction__en.srt
004 Continuing with BI, ML, and AI.mp4
004 Continuing with BI, ML, and AI__en.srt
005 A Breakdown of our Data Science Infographic.mp4
005 A Breakdown of our Data Science Infographic__en.srt
13075156-365-DataScience-Diagram.pdf
13075162-365-DataScience-Diagram.pdf
13075166-365-DataScience.png
13075168-365-DataScience.png
03 - The Field of Data Science - Connecting the Data Science Disciplines
001 Applying Traditional Data, Big Data, BI, Traditional Data Science and ML.mp4
001 Applying Traditional Data, Big Data, BI, Traditional Data Science and ML__en.srt
04 - The Field of Data Science - The Benefits of Each Discipline
001 The Reason Behind These Disciplines.mp4
001 The Reason Behind These Disciplines__en.srt
05 - The Field of Data Science - Popular Data Science Techniques
001 Techniques for Working with Traditional Data.mp4
001 Techniques for Working with Traditional Data__en.srt
002 Real Life Examples of Traditional Data.mp4
002 Real Life Examples of Traditional Data__en.srt
003 Techniques for Working with Big Data.mp4
003 Techniques for Working with Big Data__en.srt
004 Real Life Examples of Big Data.mp4
004 Real Life Examples of Big Data__en.srt
005 Business Intelligence (BI) Techniques.mp4
005 Business Intelligence (BI) Techniques__en.srt
006 Real Life Examples of Business Intelligence (BI).mp4
006 Real Life Examples of Business Intelligence (BI)__en.srt
007 Techniques for Working with Traditional Methods.mp4
007 Techniques for Working with Traditional Methods__en.srt
008 Real Life Examples of Traditional Methods.mp4
008 Real Life Examples of Traditional Methods__en.srt
009 Machine Learning (ML) Techniques.mp4
009 Machine Learning (ML) Techniques__en.srt
010 Types of Machine Learning.mp4
010 Types of Machine Learning__en.srt
011 Real Life Examples of Machine Learning (ML).mp4
011 Real Life Examples of Machine Learning (ML)__en.srt
06 - The Field of Data Science - Popular Data Science Tools
001 Necessary Programming Languages and Software Used in Data Science.mp4
001 Necessary Programming Languages and Software Used in Data Science__en.srt
07 - The Field of Data Science - Careers in Data Science
001 Finding the Job - What to Expect and What to Look for.mp4
001 Finding the Job - What to Expect and What to Look for__en.srt
08 - The Field of Data Science - Debunking Common Misconceptions
001 Debunking Common Misconceptions.mp4
001 Debunking Common Misconceptions__en.srt
09 - Part 2_ Probability
001 The Basic Probability Formula.mp4
001 The Basic Probability Formula__en.srt
002 Computing Expected Values.mp4
002 Computing Expected Values__en.srt
003 Frequency.mp4
003 Frequency__en.srt
004 Events and Their Complements.mp4
004 Events and Their Complements__en.srt
17431614-Course-Notes-Basic-Probability.pdf
10 - Probability - Combinatorics
001 Fundamentals of Combinatorics.mp4
001 Fundamentals of Combinatorics__en.srt
002 Permutations and How to Use Them.mp4
002 Permutations and How to Use Them__en.srt
003 Simple Operations with Factorials.mp4
003 Simple Operations with Factorials__en.srt
004 Solving Variations with Repetition.mp4
004 Solving Variations with Repetition__en.srt
005 Solving Variations without Repetition.mp4
005 Solving Variations without Repetition__en.srt
006 Solving Combinations.mp4
006 Solving Combinations__en.srt
007 Symmetry of Combinations.mp4
007 Symmetry of Combinations__en.srt
008 Solving Combinations with Separate Sample Spaces.mp4
008 Solving Combinations with Separate Sample Spaces__en.srt
009 Combinatorics in Real-Life_ The Lottery.mp4
009 Combinatorics in Real-Life_ The Lottery__en.srt
010 A Recap of Combinatorics.mp4
010 A Recap of Combinatorics__en.srt
011 A Practical Example of Combinatorics.mp4
011 A Practical Example of Combinatorics__en.srt
17431618-Course-Notes-Combinatorics.pdf
17431624-Symmetry-Explained.pdf
17550452-Combinations-With-Repetition.pdf
17756226-Additional-Exercises-Combinatorics.pdf
19540858-Additional-Exercises-Combinatorics-Solutions.pdf
11 - Probability - Bayesian Inference
001 Sets and Events.mp4
001 Sets and Events__en.srt
002 Ways Sets Can Interact.mp4
002 Ways Sets Can Interact__en.srt
003 Intersection of Sets.mp4
003 Intersection of Sets__en.srt
004 Union of Sets.mp4
004 Union of Sets__en.srt
005 Mutually Exclusive Sets.mp4
005 Mutually Exclusive Sets__en.srt
006 Dependence and Independence of Sets.mp4
006 Dependence and Independence of Sets__en.srt
007 The Conditional Probability Formula.mp4
007 The Conditional Probability Formula__en.srt
008 The Law of Total Probability.mp4
008 The Law of Total Probability__en.srt
009 The Additive Rule.mp4
009 The Additive Rule__en.srt
010 The Multiplication Law.mp4
010 The Multiplication Law__en.srt
011 Bayes' Law.mp4
011 Bayes' Law__en.srt
012 A Practical Example of Bayesian Inference.mp4
012 A Practical Example of Bayesian Inference__en.srt
17431622-Course-Notes-Bayesian-Inference.pdf
17970686-CDS-2017-2018-Hamilton.pdf
18886388-Bayesian-Homework.pdf
18886392-Bayesian-Homework-Solutions.pdf
GetFreeCourses.Co.url
How you can help GetFreeCourses.Co.txt
12 - Probability - Distributions
001 Fundamentals of Probability Distributions.mp4
001 Fundamentals of Probability Distributions__en.srt
002 Types of Probability Distributions.mp4
002 Types of Probability Distributions__en.srt
003 Characteristics of Discrete Distributions.mp4
003 Characteristics of Discrete Distributions__en.srt
004 Discrete Distributions_ The Uniform Distribution.mp4
004 Discrete Distributions_ The Uniform Distribution__en.srt
005 Discrete Distributions_ The Bernoulli Distribution.mp4
005 Discrete Distributions_ The Bernoulli Distribution__en.srt
006 Discrete Distributions_ The Binomial Distribution.mp4
006 Discrete Distributions_ The Binomial Distribution__en.srt
007 Discrete Distributions_ The Poisson Distribution.mp4
007 Discrete Distributions_ The Poisson Distribution__en.srt
008 Characteristics of Continuous Distributions.mp4
008 Characteristics of Continuous Distributions__en.srt
009 Continuous Distributions_ The Normal Distribution.mp4
009 Continuous Distributions_ The Normal Distribution__en.srt
010 Continuous Distributions_ The Standard Normal Distribution.mp4
010 Continuous Distributions_ The Standard Normal Distribution__en.srt
011 Continuous Distributions_ The Students' T Distribution.mp4
011 Continuous Distributions_ The Students' T Distribution__en.srt
012 Continuous Distributions_ The Chi-Squared Distribution.mp4
012 Continuous Distributions_ The Chi-Squared Distribution__en.srt
013 Continuous Distributions_ The Exponential Distribution.mp4
013 Continuous Distributions_ The Exponential Distribution__en.srt
014 Continuous Distributions_ The Logistic Distribution.mp4
014 Continuous Distributions_ The Logistic Distribution__en.srt
015 A Practical Example of Probability Distributions.mp4
015 A Practical Example of Probability Distributions__en.srt
17431628-Solving-Integrals.pdf
17550252-Normal-Distribution-Exp-and-Var.pdf
17862366-Poisson-Expected-Value-and-Variance.pdf
17971238-FIFA19.csv
17971248-FIFA19-post.csv
17971258-Daily-Views.xlsx
17971260-Daily-Views-post.xlsx
17971264-Customers-Membership.xlsx
17971268-Customers-Membership-post.xlsx
20945990-Course-Notes-Probability-Distributions.pdf
13 - Probability - Probability in Other Fields
001 Probability in Finance.mp4
001 Probability in Finance__en.srt
002 Probability in Statistics.mp4
002 Probability in Statistics__en.srt
003 Probability in Data Science.mp4
003 Probability in Data Science__en.srt
19327638-Probability-in-Finance-Homework.pdf
19327648-Probability-in-Finance-Solutions.pdf
23224540-Probability-Cheat-Sheet.pdf
14 - Part 3_ Statistics
001 Population and Sample.mp4
001 Population and Sample__en.srt
14812652-Course-notes-descriptive-statistics.pdf
15762096-Statistics-Glossary.xlsx
15 - Statistics - Descriptive Statistics
001 Types of Data.mp4
001 Types of Data__en.srt
002 Levels of Measurement.mp4
002 Levels of Measurement__en.srt
003 Categorical Variables - Visualization Techniques.mp4
003 Categorical Variables - Visualization Techniques__en.srt
004 Categorical Variables Exercise.html
005 Numerical Variables - Frequency Distribution Table.mp4
005 Numerical Variables - Frequency Distribution Table__en.srt
006 Numerical Variables Exercise.html
007 The Histogram.mp4
007 The Histogram__en.srt
008 Histogram Exercise.html
009 Cross Tables and Scatter Plots.mp4
009 Cross Tables and Scatter Plots__en.srt
010 Cross Tables and Scatter Plots Exercise.html
011 Mean, median and mode.mp4
011 Mean, median and mode__en.srt
012 Mean, Median and Mode Exercise.html
013 Skewness.mp4
013 Skewness__en.srt
014 Skewness Exercise.html
015 Variance.mp4
015 Variance__en.srt
016 Variance Exercise.html
017 Standard Deviation and Coefficient of Variation.mp4
017 Standard Deviation and Coefficient of Variation__en.srt
018 Standard Deviation and Coefficient of Variation Exercise.html
019 Covariance.mp4
019 Covariance__en.srt
020 Covariance Exercise.html
021 Correlation Coefficient.mp4
021 Correlation Coefficient__en.srt
022 Correlation Coefficient Exercise.html
13055412-2.3.Categorical-variables.Visualization-techniques-exercise.xlsx
13055414-2.3.Categorical-variables.Visualization-techniques-exercise-solution.xlsx
13055440-2.5.The-Histogram-lesson.xlsx
13055456-2.6.Cross-table-and-scatter-plot.xlsx
13055460-2.6.Cross-table-and-scatter-plot-exercise.xlsx
13055464-2.6.Cross-table-and-scatter-plot-exercise-solution.xlsx
13055474-2.7.Mean-median-and-mode-lesson.xlsx
13055484-2.7.Mean-median-and-mode-exercise.xlsx
13055486-2.7.Mean-median-and-mode-exercise-solution.xlsx
13055492-2.8.Skewness-lesson.xlsx
13055500-2.8.Skewness-exercise.xlsx
13055502-2.8.Skewness-exercise-solution.xlsx
13055510-2.9.Variance-lesson.xlsx
13055516-2.9.Variance-exercise.xlsx
13055520-2.9.Variance-exercise-solution.xlsx
13055774-2.3.Categorical-variables.Visualization-techniques-lesson.xlsx
13055786-2.5.The-Histogram-exercise.xlsx
13055790-2.5.The-Histogram-exercise-solution.xlsx
13055800-2.10.Standard-deviation-and-coefficient-of-variation-lesson.xlsx
13055814-2.11.Covariance-lesson.xlsx
13055822-2.11.Covariance-exercise.xlsx
13055824-2.11.Covariance-exercise-solution.xlsx
13055834-2.12.Correlation-exercise.xlsx
13055838-2.12.Correlation-exercise-solution.xlsx
14679830-2.4.Numerical-variables.Frequency-distribution-table-lesson.xlsx
14812660-Course-notes-descriptive-statistics.pdf
16753694-Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf
16753696-Statistics-PDF-with-Excel-Solutions-that-dont-visualize-properly.pdf
18029224-Glossary.xlsx
19880121-2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx
19880123-2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx
23038654-2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx
16 - Statistics - Practical Example_ Descriptive Statistics
001 Practical Example_ Descriptive Statistics.mp4
001 Practical Example_ Descriptive Statistics__en.srt
002 Practical Example_ Descriptive Statistics Exercise.html
13129220-2.13.Practical-example.Descriptive-statistics-lesson.xlsx
19527574-2.13.Practical-example.Descriptive-statistics-exercise.xlsx
19527576-2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx
17 - Statistics - Inferential Statistics Fundamentals
001 Introduction.mp4
001 Introduction__en.srt
002 What is a Distribution.mp4
002 What is a Distribution__en.srt
003 The Normal Distribution.mp4
003 The Normal Distribution__en.srt
004 The Standard Normal Distribution.mp4
004 The Standard Normal Distribution__en.srt
005 The Standard Normal Distribution Exercise.html
006 Central Limit Theorem.mp4
006 Central Limit Theorem__en.srt
007 Standard error.mp4
007 Standard error__en.srt
008 Estimators and Estimates.mp4
008 Estimators and Estimates__en.srt
13055898-3.2.What-is-a-distribution-lesson.xlsx
13055942-3.4.Standard-normal-distribution-lesson.xlsx
13831264-Course-notes-inferential-statistics.pdf
13831266-Course-notes-inferential-statistics.pdf
14171114-3.4.Standard-normal-distribution-exercise.xlsx
14171118-3.4.Standard-normal-distribution-exercise-solution.xlsx
18 - Statistics - Inferential Statistics_ Confidence Intervals
001 What are Confidence Intervals_.mp4
001 What are Confidence Intervals___en.srt
002 Confidence Intervals; Population Variance Known; Z-score.mp4
002 Confidence Intervals; Population Variance Known; Z-score__en.srt
003 Confidence Intervals; Population Variance Known; Z-score; Exercise.html
004 Confidence Interval Clarifications.mp4
004 Confidence Interval Clarifications__en.srt
005 Student's T Distribution.mp4
005 Student's T Distribution__en.srt
006 Confidence Intervals; Population Variance Unknown; T-score.mp4
006 Confidence Intervals; Population Variance Unknown; T-score__en.srt
007 Confidence Intervals; Population Variance Unknown; T-score; Exercise.html
008 Margin of Error.mp4
008 Margin of Error__en.srt
009 Confidence intervals. Two means. Dependent samples.mp4
009 Confidence intervals. Two means. Dependent samples__en.srt
010 Confidence intervals. Two means. Dependent samples Exercise.html
011 Confidence intervals. Two means. Independent Samples (Part 1).mp4
011 Confidence intervals. Two means. Independent Samples (Part 1)__en.srt
012 Confidence intervals. Two means. Independent Samples (Part 1). Exercise.html
013 Confidence intervals. Two means. Independent Samples (Part 2).mp4
013 Confidence intervals. Two means. Independent Samples (Part 2)__en.srt
014 Confidence intervals. Two means. Independent Samples (Part 2). Exercise.html
015 Confidence intervals. Two means. Independent Samples (Part 3).mp4
015 Confidence intervals. Two means. Independent Samples (Part 3)__en.srt
13056180-3.9.Population-variance-known-z-score-lesson.xlsx
13056196-3.9.Population-variance-known-z-score-exercise.xlsx
13056200-3.9.Population-variance-known-z-score-exercise-solution.xlsx
13056212-3.11.Population-variance-unknown-t-score-lesson.xlsx
13056216-3.11.The-t-table.xlsx
13056226-3.11.Population-variance-unknown-t-score-exercise.xlsx
13056228-3.11.Population-variance-unknown-t-score-exercise-solution.xlsx
13056236-3.13.Confidence-intervals.Two-means.Dependent-samples-lesson.xlsx
13056246-3.13.Confidence-intervals.Two-means.Dependent-samples-exercise.xlsx
13056252-3.13.Confidence-intervals.Two-means.Dependent-samples-exercise-solution.xlsx
13056280-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-lesson.xlsx
13056290-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise.xlsx
13056292-3.14.Confidence-intervals.Two-means.Independent-samples-Part-1-exercise-solution.xlsx
13056308-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-lesson.xlsx
13056316-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise.xlsx
13056318-3.15.Confidence-intervals.Two-means.Independent-samples-Part-2-exercise-solution.xlsx
16413674-3.9.The-z-table.xlsx
16413678-3.9.The-z-table.xlsx
21198408-3.11.The-t-table.xlsx
19 - Statistics - Practical Example_ Inferential Statistics
001 Practical Example_ Inferential Statistics.mp4
001 Practical Example_ Inferential Statistics__en.srt
002 Practical Example_ Inferential Statistics Exercise.html
13056326-3.17.Practical-example.Confidence-intervals-lesson.xlsx
17959056-3.17.Practical-example.Confidence-intervals-exercise.xlsx
17959058-3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx
20 - Statistics - Hypothesis Testing
001 Null vs Alternative Hypothesis.mp4
001 Null vs Alternative Hypothesis__en.srt
002 Further Reading on Null and Alternative Hypothesis.html
003 Rejection Region and Significance Level.mp4
003 Rejection Region and Significance Level__en.srt
004 Type I Error and Type II Error.mp4
004 Type I Error and Type II Error__en.srt
005 Test for the Mean. Population Variance Known.mp4
005 Test for the Mean. Population Variance Known__en.srt
006 Test for the Mean. Population Variance Known Exercise.html
007 p-value.mp4
007 p-value__en.srt
008 Test for the Mean. Population Variance Unknown.mp4
008 Test for the Mean. Population Variance Unknown__en.srt
009 Test for the Mean. Population Variance Unknown Exercise.html
010 Test for the Mean. Dependent Samples.mp4
010 Test for the Mean. Dependent Samples__en.srt
011 Test for the Mean. Dependent Samples Exercise.html
012 Test for the mean. Independent Samples (Part 1).mp4
012 Test for the mean. Independent Samples (Part 1)__en.srt
013 Test for the mean. Independent Samples (Part 1). Exercise.html
014 Test for the mean. Independent Samples (Part 2).mp4
014 Test for the mean. Independent Samples (Part 2)__en.srt
015 Test for the mean. Independent Samples (Part 2). Exercise.html
13056520-4.4.Test-for-the-mean.Population-variance-known-lesson.xlsx
13056684-4.4.Test-for-the-mean.Population-variance-known-exercise.xlsx
13056688-4.4.Test-for-the-mean.Population-variance-known-exercise-solution.xlsx
13056708-4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx
13056712-4.7.Test-for-the-mean.Dependent-samples-lesson.xlsx
13056716-4.7.Test-for-the-mean.Dependent-samples-exercise.xlsx
13056718-4.7.Test-for-the-mean.Dependent-samples-exercise-solution.xlsx
13056720-4.8.Test-for-the-mean.Independent-samples-Part-1-lesson.xlsx
13056726-4.9.Test-for-the-mean.Independent-samples-Part-2-lesson.xlsx
13737052-4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx
16190540-4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx
16190542-4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx
16200120-4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx
16753580-Online-p-value-calculator.pdf
17710210-4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx
18041220-4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx
22431075-Course-notes-hypothesis-testing.pdf
22431079-Course-notes-hypothesis-testing.pdf
21 - Statistics - Practical Example_ Hypothesis Testing
001 Practical Example_ Hypothesis Testing.mp4
001 Practical Example_ Hypothesis Testing__en.srt
002 Practical Example_ Hypothesis Testing Exercise.html
27047254-4.10.Hypothesis-testing-section-practical-example.xlsx
27047330-4.10.Hypothesis-testing-section-practical-example-exercise.xlsx
27047334-4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx
22 - Part 4_ Introduction to Python
001 Introduction to Programming.mp4
001 Introduction to Programming__en.srt
002 Why Python_.mp4
002 Why Python___en.srt
003 Why Jupyter_.mp4
003 Why Jupyter___en.srt
004 Installing Python and Jupyter.mp4
004 Installing Python and Jupyter__en.srt
005 Understanding Jupyter's Interface - the Notebook Dashboard.mp4
005 Understanding Jupyter's Interface - the Notebook Dashboard__en.srt
006 Prerequisites for Coding in the Jupyter Notebooks.mp4
006 Prerequisites for Coding in the Jupyter Notebooks__en.srt
23 - Python - Variables and Data Types
001 Variables.mp4
001 Variables__en.srt
002 Numbers and Boolean Values in Python.mp4
002 Numbers and Boolean Values in Python__en.srt
003 Python Strings.mp4
003 Python Strings__en.srt
15870664-Python-Introduction-Course-Notes.pdf
29544526-Variables-Lecture-Py3.ipynb
29544572-Numbers-and-Boolean-Values-Lecture-Py3.ipynb
29544578-Strings-Lecture-Py3.ipynb
29544582-Strings-Exercise-Py3.ipynb
29544586-Strings-Solution-Py3.ipynb
29544590-Numbers-and-Boolean-Values-Exercise-Py3.ipynb
29544594-Numbers-and-Boolean-Values-Solution-Py3.ipynb
29544602-Variables-Exercise-Py3.ipynb
29544612-Variables-Solution-Py3.ipynb
24 - Python - Basic Python Syntax
001 Using Arithmetic Operators in Python.mp4
001 Using Arithmetic Operators in Python__en.srt
002 The Double Equality Sign.mp4
002 The Double Equality Sign__en.srt
003 How to Reassign Values.mp4
003 How to Reassign Values__en.srt
004 Add Comments.mp4
004 Add Comments__en.srt
005 Understanding Line Continuation.mp4
005 Understanding Line Continuation__en.srt
006 Indexing Elements.mp4
006 Indexing Elements__en.srt
007 Structuring with Indentation.mp4
007 Structuring with Indentation__en.srt
29544616-Arithmetic-Operators-Lecture-Py3.ipynb
29544618-Arithmetic-Operators-Exercise-Py3.ipynb
29544620-Arithmetic-Operators-Solution-Py3.ipynb
29544624-The-Double-Equality-Sign-Lecture-Py3.ipynb
29544630-The-Double-Equality-Sign-Exercise-Py3.ipynb
29544632-The-Double-Equality-Sign-Solution-Py3.ipynb
29544648-Reassign-Values-Lecture-Py3.ipynb
29544656-Reassign-Values-Exercise-Py3.ipynb
29544658-Reassign-Values-Solution-Py3.ipynb
29544678-Add-Comments-Lecture-Py3.ipynb
29544682-Indexing-Elements-Lecture-Py3.ipynb
29544684-Indexing-Elements-Exercise-Py3.ipynb
29544694-Indexing-Elements-Solution-Py3.ipynb
29544712-Line-Continuation-Lecture-Py3.ipynb
29544714-Line-Continuation-Exercise-Py3.ipynb
29544716-Line-Continuation-Solution-Py3.ipynb
29544720-Structure-Your-Code-with-Indentation-Lecture-Py3.ipynb
29544724-Structure-Your-Code-with-Indentation-Exercise-Py3.ipynb
29544728-Structure-Your-Code-with-Indentation-Solution-Py3.ipynb
GetFreeCourses.Co.url
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25 - Python - Other Python Operators
001 Comparison Operators.mp4
001 Comparison Operators__en.srt
002 Logical and Identity Operators.mp4
002 Logical and Identity Operators__en.srt
29544734-Comparison-Operators-Lecture-Py3.ipynb
29544738-Comparison-Operators-Exercise-Py3.ipynb
29544744-Comparison-Operators-Solution-Py3.ipynb
29544754-Logical-and-Identity-Operators-Lecture-Py3.ipynb
29544770-Logical-and-Identity-Operators-Lecture-Py3.ipynb
29544776-Logical-and-Identity-Operators-Solution-Py3.ipynb
26 - Python - Conditional Statements
001 The IF Statement.mp4
001 The IF Statement__en.srt
002 The ELSE Statement.mp4
002 The ELSE Statement__en.srt
003 The ELIF Statement.mp4
003 The ELIF Statement__en.srt
004 A Note on Boolean Values.mp4
004 A Note on Boolean Values__en.srt
29544784-Introduction-to-the-If-Statement-Lecture-Py3.ipynb
29544788-Introduction-to-the-If-Statement-Exercise-Py3.ipynb
29544792-Introduction-to-the-If-Statement-Solution-Py3.ipynb
29544796-Add-an-Else-Statement-Lecture-Py3.ipynb
29544802-Add-an-Else-Statement-Exercise-Py3.ipynb
29544804-Add-an-Else-Statement-Solution-Py3.ipynb
29544814-Else-If-for-Brief-Elif-Lecture-Py3.ipynb
29544818-Else-If-for-Brief-Elif-Exercise-Py3.ipynb
29544822-Else-If-for-Brief-Elif-Solution-Py3.ipynb
29544828-A-Note-on-Boolean-Values-Lecture-Py3.ipynb
27 - Python - Python Functions
001 Defining a Function in Python.mp4
001 Defining a Function in Python__en.srt
002 How to Create a Function with a Parameter.mp4
002 How to Create a Function with a Parameter__en.srt
003 Defining a Function in Python - Part II.mp4
003 Defining a Function in Python - Part II__en.srt
004 How to Use a Function within a Function.mp4
004 How to Use a Function within a Function__en.srt
005 Conditional Statements and Functions.mp4
005 Conditional Statements and Functions__en.srt
006 Functions Containing a Few Arguments.mp4
006 Functions Containing a Few Arguments__en.srt
007 Built-in Functions in Python.mp4
007 Built-in Functions in Python__en.srt
29544842-Defining-a-Function-in-Python-Lecture-Py3.ipynb
29544846-Creating-a-Function-with-a-Parameter-Lecture-Py3.ipynb
29544848-Creating-a-Function-with-a-Parameter-Exercise-Py3.ipynb
29544850-Creating-a-Function-with-a-Parameter-Solution-Py3.ipynb
29544866-Another-Way-to-Define-a-Function-Lecture-Py3.ipynb
29544868-Another-Way-to-Define-a-Function-Exercise-Py3.ipynb
29544874-Another-Way-to-Define-a-Function-Solution-Py3.ipynb
29544880-0.6.4-Using-a-Function-in-another-Function-Lecture-Py3.ipynb
29544888-0.6.4-Using-a-Function-in-another-Function-Exercise-Py3.ipynb
29544890-0.6.4-Using-a-Function-in-another-Function-Solution-Py3.ipynb
29544904-Combining-Conditional-Statements-and-Functions-Lecture-Py3.ipynb
29544906-Combining-Conditional-Statements-and-Functions-Exercise-Py3.ipynb
29544910-Combining-Conditional-Statements-and-Functions-Solution-Py3.ipynb
29544920-Creating-Functions-Containing-a-Few-Arguments-Lecture-Py3.ipynb
29544922-Notable-Built-In-Functions-in-Python-Lecture-Py3.ipynb
29544924-Notable-Built-In-Functions-in-Python-Exercise-Py3.ipynb
29544926-Notable-Built-In-Functions-in-Python-Solution-Py3.ipynb
28 - Python - Sequences
001 Lists.mp4
001 Lists__en.srt
002 Using Methods.mp4
002 Using Methods__en.srt
003 List Slicing.mp4
003 List Slicing__en.srt
004 Tuples.mp4
004 Tuples__en.srt
005 Dictionaries.mp4
005 Dictionaries__en.srt
29544928-Lists-Lecture-Py3.ipynb
29544930-Lists-Exercise-Py3.ipynb
29544932-Lists-Solution-Py3.ipynb
29544938-Help-Yourself-with-Methods-Lecture-Py3.ipynb
29544942-Help-Yourself-with-Methods-Exercise-Py3.ipynb
29544946-Help-Yourself-with-Methods-Solution-Py3.ipynb
29544952-List-Slicing-Lecture-Py3.ipynb
29544956-List-Slicing-Exercise-Py3.ipynb
29544960-List-Slicing-Solution-Py3.ipynb
29544972-Tuples-Lecture-Py3.ipynb
29544976-Tuples-Exercise-Py3.ipynb
29544978-Tuples-Solution-Py3.ipynb
29544988-Dictionaries-Lecture-Py3.ipynb
29544992-Dictionaries-Exercise-Py3.ipynb
29544994-Dictionaries-Solution-Py3.ipynb
29 - Python - Iterations
001 For Loops.mp4
001 For Loops__en.srt
002 While Loops and Incrementing.mp4
002 While Loops and Incrementing__en.srt
003 Lists with the range() Function.mp4
003 Lists with the range() Function__en.srt
004 Conditional Statements and Loops.mp4
004 Conditional Statements and Loops__en.srt
005 Conditional Statements, Functions, and Loops.mp4
005 Conditional Statements, Functions, and Loops__en.srt
006 How to Iterate over Dictionaries.mp4
006 How to Iterate over Dictionaries__en.srt
29545008-For-Loops-Lecture-Py3.ipynb
29545010-For-Loops-Exercise-Py3.ipynb
29545018-For-Loops-Solution-Py3.ipynb
29545028-While-Loops-and-Incrementing-Lecture-Py3.ipynb
29545030-While-Loops-and-Incrementing-Exercise-Py3.ipynb
29545032-While-Loops-and-Incrementing-Solution-Py3.ipynb
29545042-Create-Lists-with-the-range-Function-Lecture-Py3.ipynb
29545046-Create-Lists-with-the-range-Function-Exercise-Py3.ipynb
29545048-Create-Lists-with-the-range-Function-Solution-Py3.ipynb
29545058-Use-Conditional-Statements-and-Loops-Together-Lecture-Py3.ipynb
29545070-Use-Conditional-Statements-and-Loops-Together-Exercise-Py3.ipynb
29545074-Use-Conditional-Statements-and-Loops-Together-Solution-Py3.ipynb
29545092-All-In-Lecture-Py3.ipynb
29545100-All-In-Exercise-Py3.ipynb
29545102-All-In-Solution-Py3.ipynb
29545116-Iterating-over-Dictionaries-Lecture-Py3.ipynb
29545118-Iterating-over-Dictionaries-Exercise-Py3.ipynb
29545120-Iterating-over-Dictionaries-Solution-Py3.ipynb
30 - Python - Advanced Python Tools
001 Object Oriented Programming.mp4
001 Object Oriented Programming__en.srt
002 Modules and Packages.mp4
002 Modules and Packages__en.srt
003 What is the Standard Library_.mp4
003 What is the Standard Library___en.srt
004 Importing Modules in Python.mp4
004 Importing Modules in Python__en.srt
31 - Part 5_ Advanced Statistical Methods in Python
001 Introduction to Regression Analysis.mp4
001 Introduction to Regression Analysis__en.srt
22685780-Course-notes-regression-analysis.pdf
32 - Advanced Statistical Methods - Linear Regression with StatsModels
001 The Linear Regression Model.mp4
001 The Linear Regression Model__en.srt
002 Correlation vs Regression.mp4
002 Correlation vs Regression__en.srt
003 Geometrical Representation of the Linear Regression Model.mp4
003 Geometrical Representation of the Linear Regression Model__en.srt
004 Python Packages Installation.mp4
004 Python Packages Installation__en.srt
004 Python Packages Installation_en.vtt
005 First Regression in Python.mp4
005 First Regression in Python__en.srt
006 First Regression in Python Exercise.html
007 Using Seaborn for Graphs.mp4
007 Using Seaborn for Graphs__en.srt
008 How to Interpret the Regression Table.mp4
008 How to Interpret the Regression Table__en.srt
009 Decomposition of Variability.mp4
009 Decomposition of Variability__en.srt
010 What is the OLS_.mp4
010 What is the OLS___en.srt
011 R-Squared.mp4
011 R-Squared__en.srt
22685784-Course-notes-regression-analysis.pdf
29587970-1.01.Simple-linear-regression.csv
29587976-Simple-linear-regression.ipynb
29588016-Simple-linear-regression-with-comments.ipynb
29588022-real-estate-price-size.csv
29588024-Simple-Linear-Regression-Exercise-Solution.ipynb
29588026-Simple-Linear-Regression-Exercise.ipynb
33 - Advanced Statistical Methods - Multiple Linear Regression with StatsModels
001 Multiple Linear Regression.mp4
001 Multiple Linear Regression__en.srt
002 Adjusted R-Squared.mp4
002 Adjusted R-Squared__en.srt
003 Multiple Linear Regression Exercise.html
004 Test for Significance of the Model (F-Test).mp4
004 Test for Significance of the Model (F-Test)__en.srt
005 OLS Assumptions.mp4
005 OLS Assumptions__en.srt
006 A1_ Linearity.mp4
006 A1_ Linearity__en.srt
007 A2_ No Endogeneity.mp4
007 A2_ No Endogeneity__en.srt
008 A3_ Normality and Homoscedasticity.mp4
008 A3_ Normality and Homoscedasticity__en.srt
009 A4_ No Autocorrelation.mp4
009 A4_ No Autocorrelation__en.srt
010 A5_ No Multicollinearity.mp4
010 A5_ No Multicollinearity__en.srt
011 Dealing with Categorical Data - Dummy Variables.mp4
011 Dealing with Categorical Data - Dummy Variables__en.srt
012 Dealing with Categorical Data - Dummy Variables.html
013 Making Predictions with the Linear Regression.mp4
013 Making Predictions with the Linear Regression__en.srt
29588058-1.02.Multiple-linear-regression.csv
29588064-Multiple-linear-regression-and-Adjusted-R-squared.ipynb
29588066-Multiple-linear-regression-and-Adjusted-R-squared-with-comments.ipynb
29588068-Multiple-Linear-Regression-Exercise-Solution.ipynb
29588072-Multiple-Linear-Regression-Exercise.ipynb
29588076-real-estate-price-size-year.csv
29588090-1.03.Dummies.csv
29588094-Dummy-Variables.ipynb
29588120-Dummy-variables-with-comments.ipynb
29588124-Multiple-Linear-Regression-with-Dummies-Exercise-Solution.ipynb
29588128-Multiple-Linear-Regression-with-Dummies-Exercise.ipynb
29588130-real-estate-price-size-year-view.csv
29588138-Making-predictions.ipynb
29588142-Making-predictions-with-comments.ipynb
34 - Advanced Statistical Methods - Linear Regression with sklearn
001 What is sklearn and How is it Different from Other Packages.mp4
001 What is sklearn and How is it Different from Other Packages__en.srt
002 How are we Going to Approach this Section_.mp4
002 How are we Going to Approach this Section___en.srt
002 How are we Going to Approach this Section__en.vtt
003 Simple Linear Regression with sklearn.mp4
003 Simple Linear Regression with sklearn__en.srt
003 Simple Linear Regression with sklearn_en.vtt
004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table.mp4
004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table__en.srt
004 Simple Linear Regression with sklearn - A StatsModels-like Summary Table_en.vtt
005 A Note on Normalization.html
006 Simple Linear Regression with sklearn - Exercise.html
007 Multiple Linear Regression with sklearn.mp4
007 Multiple Linear Regression with sklearn__en.srt
007 Multiple Linear Regression with sklearn_en.vtt
008 Calculating the Adjusted R-Squared in sklearn.mp4
008 Calculating the Adjusted R-Squared in sklearn__en.srt
009 Calculating the Adjusted R-Squared in sklearn - Exercise.html
010 Feature Selection (F-regression).mp4
010 Feature Selection (F-regression)__en.srt
011 A Note on Calculation of P-values with sklearn.html
012 Creating a Summary Table with P-values.mp4
012 Creating a Summary Table with P-values__en.srt
013 Multiple Linear Regression - Exercise.html
014 Feature Scaling (Standardization).mp4
014 Feature Scaling (Standardization)__en.srt
015 Feature Selection through Standardization of Weights.mp4
015 Feature Selection through Standardization of Weights__en.srt
016 Predicting with the Standardized Coefficients.mp4
016 Predicting with the Standardized Coefficients__en.srt
017 Feature Scaling (Standardization) - Exercise.html
018 Underfitting and Overfitting.mp4
018 Underfitting and Overfitting__en.srt
019 Train - Test Split Explained.mp4
019 Train - Test Split Explained__en.srt
29588160-1.01.Simple-linear-regression.csv
29588164-sklearn-Simple-Linear-Regression.ipynb
29588166-sklearn-Simple-Linear-Regression-with-comments.ipynb
29588200-1.01.Simple-linear-regression.csv
29588206-sklearn-Simple-Linear-Regression.ipynb
29588208-sklearn-Simple-Linear-Regression-with-comments.ipynb
29588240-1.02.Multiple-linear-regression.csv
29588244-sklearn-Multiple-Linear-Regression.ipynb
29588246-sklearn-Multiple-Linear-Regression-with-comments.ipynb
29588306-1.02.Multiple-linear-regression.csv
29588310-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared.ipynb
29588312-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-with-comments.ipynb
29588320-1.02.Multiple-linear-regression.csv
29588324-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise-Solution.ipynb
29588328-sklearn-Multiple-Linear-Regression-and-Adjusted-R-squared-Exercise.ipynb
29588334-1.02.Multiple-linear-regression.csv
29588340-sklearn-Feature-Selection-with-F-regression.ipynb
29588342-sklearn-Feature-Selection-with-F-regression-with-comments.ipynb
29588350-1.02.Multiple-linear-regression.csv
29588358-sklearn-How-to-properly-include-p-values.ipynb
29588366-1.02.Multiple-linear-regression.csv
29588370-sklearn-Multiple-Linear-Regression-Summary-Table.ipynb
29588372-sklearn-Multiple-Linear-Regression-Summary-Table-with-comments.ipynb
29588378-real-estate-price-size-year.csv
29588380-sklearn-Multiple-Linear-Regression-Exercise-Solution.ipynb
29588382-sklearn-Multiple-Linear-Regression-Exercise.ipynb
29588388-1.02.Multiple-linear-regression.csv
29588392-sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-1.ipynb
29588394-SKLEAR-1.IPY
29588398-1.02.Multiple-linear-regression.csv
29588400-sklearn-Feature-Selection-through-Feature-Scaling-Standardization-Part-2.ipynb
29588412-SKLEAR-1.IPY
29588414-1.02.Multiple-linear-regression.csv
29588416-sklearn-Making-Predictions-with-the-Standardized-Coefficients.ipynb
29588422-sklearn-Making-Predictions-with-the-Standardized-Coefficients-with-comments.ipynb
29588430-real-estate-price-size-year.csv
29588432-sklearn-Feature-Scaling-Exercise-Solution.ipynb
29588434-sklearn-Feature-Scaling-Exercise.ipynb
29588436-sklearn-Train-Test-Split.ipynb
29588440-sklearn-Train-Test-Split-with-comments.ipynb
33130180-real-estate-price-size.csv
33130182-Simple-Linear-Regression-with-sklearn-Exercise.ipynb
33130186-Simple-Linear-Regression-with-sklearn-Exercise-Solution.ipynb
GetFreeCourses.Co.url
How you can help GetFreeCourses.Co.txt
35 - Advanced Statistical Methods - Practical Example_ Linear Regression
001 Practical Example_ Linear Regression (Part 1).mp4
001 Practical Example_ Linear Regression (Part 1)__en.srt
002 Practical Example_ Linear Regression (Part 2).mp4
002 Practical Example_ Linear Regression (Part 2)__en.srt
002 Practical Example_ Linear Regression (Part 2)_en.vtt
003 A Note on Multicollinearity.html
004 Practical Example_ Linear Regression (Part 3).mp4
004 Practical Example_ Linear Regression (Part 3)__en.srt
005 Dummies and Variance Inflation Factor - Exercise.html
006 Practical Example_ Linear Regression (Part 4).mp4
006 Practical Example_ Linear Regression (Part 4)__en.srt
007 Dummy Variables - Exercise.html
008 Practical Example_ Linear Regression (Part 5).mp4
008 Practical Example_ Linear Regression (Part 5)__en.srt
009 Linear Regression - Exercise.html
29588446-1.04.Real-life-example.csv
29588452-sklearn-Linear-Regression-Practical-Example-Part-1.ipynb
29588454-sklearn-Linear-Regression-Practical-Example-Part-1-with-comments.ipynb
29588460-1.04.Real-life-example.csv
29588462-sklearn-Linear-Regression-Practical-Example-Part-2.ipynb
29588466-sklearn-Linear-Regression-Practical-Example-Part-2-with-comments.ipynb
29588552-sklearn-Linear-Regression-Practical-Example-Part-3.ipynb
29588558-sklearn-Linear-Regression-Practical-Example-Part-3-with-comments.ipynb
29588598-1.04.Real-life-example.csv
29588602-sklearn-Dummies-and-VIF-Exercise-Solution.ipynb
29588604-sklearn-Dummies-and-VIF-Exercise.ipynb
29588606-1.04.Real-life-example.csv
29588612-sklearn-Linear-Regression-Practical-Example-Part-4.ipynb
29588618-sklearn-Linear-Regression-Practical-Example-Part-4-with-comments.ipynb
29588624-1.04.Real-life-example.csv
29588626-sklearn-Linear-Regression-Practical-Example-Part-5.ipynb
29588630-sklearn-Linear-Regression-Practical-Example-Part-5-with-comments.ipynb
external-assets-links.txt
36 - Advanced Statistical Methods - Logistic Regression
001 Introduction to Logistic Regression.mp4
001 Introduction to Logistic Regression__en.srt
002 A Simple Example in Python.mp4
002 A Simple Example in Python__en.srt
003 Logistic vs Logit Function.mp4
003 Logistic vs Logit Function__en.srt
004 Building a Logistic Regression.mp4
004 Building a Logistic Regression__en.srt
005 Building a Logistic Regression - Exercise.html
006 An Invaluable Coding Tip.mp4
006 An Invaluable Coding Tip__en.srt
007 Understanding Logistic Regression Tables.mp4
007 Understanding Logistic Regression Tables__en.srt
008 Understanding Logistic Regression Tables - Exercise.html
009 What do the Odds Actually Mean.mp4
009 What do the Odds Actually Mean__en.srt
010 Binary Predictors in a Logistic Regression.mp4
010 Binary Predictors in a Logistic Regression__en.srt
011 Binary Predictors in a Logistic Regression - Exercise.html
012 Calculating the Accuracy of the Model.mp4
012 Calculating the Accuracy of the Model__en.srt
013 Calculating the Accuracy of the Model.html
014 Underfitting and Overfitting.mp4
014 Underfitting and Overfitting__en.srt
015 Testing the Model.mp4
015 Testing the Model__en.srt
016 Testing the Model - Exercise.html
15451783-Example-bank-data.csv
15451889-Bank-data.csv
15451939-Bank-data.csv
15451967-Bank-data.csv
15452033-Bank-data.csv
15452035-Bank-data-testing.csv
23412976-Course-Notes-Logistic-Regression.pdf
23413016-Course-Notes-Logistic-Regression.pdf
29588638-2.01.Admittance.csv
29588642-Admittance.ipynb
29588644-Admittance-with-comments.ipynb
29588660-Admittance-regression-tables-fixed-error.ipynb
29588666-Admittance-regression.ipynb
29588668-Admittance-regression-summary-error.ipynb
29588676-Building-a-Logistic-Regression-Exercise.ipynb
29588678-Building-a-Logistic-Regression-Solution.ipynb
29588694-Understanding-Logistic-Regression-Tables-Exercise.ipynb
29588700-Understanding-Logistic-Regression-Tables-Solution.ipynb
29588712-2.02.Binary-predictors.csv
29588716-Binary-predictors.ipynb
29588826-Binary-Predictors-in-a-Logistic-Regression-Exercise.ipynb
29588832-Binary-Predictors-in-a-Logistic-Regression-Solution.ipynb
29588838-Accuracy.ipynb
29588842-Accuracy-with-comments.ipynb
29588854-Calculating-the-Accuracy-of-the-Model-Exercise.ipynb
29588856-Calculating-the-Accuracy-of-the-Model-Solution.ipynb
29588864-Testing-the-model.ipynb
29588872-2.03.Test-dataset.csv
29588876-Testing-the-model-with-comments.ipynb
29588894-Testing-the-Model-Exercise.ipynb
29588898-Testing-the-Model-Solution.ipynb
37 - Advanced Statistical Methods - Cluster Analysis
001 Introduction to Cluster Analysis.mp4
001 Introduction to Cluster Analysis__en.srt
002 Some Examples of Clusters.mp4
002 Some Examples of Clusters__en.srt
003 Difference between Classification and Clustering.mp4
003 Difference between Classification and Clustering__en.srt
004 Math Prerequisites.mp4
004 Math Prerequisites__en.srt
23413656-Course-Notes-Cluster-Analysis.pdf
23413662-Course-Notes-Cluster-Analysis.pdf
38 - Advanced Statistical Methods - K-Means Clustering
001 K-Means Clustering.mp4
001 K-Means Clustering__en.srt
002 A Simple Example of Clustering.mp4
002 A Simple Example of Clustering__en.srt
002 A Simple Example of Clustering_en.vtt
003 A Simple Example of Clustering - Exercise.html
004 Clustering Categorical Data.mp4
004 Clustering Categorical Data__en.srt
005 Clustering Categorical Data - Exercise.html
006 How to Choose the Number of Clusters.mp4
006 How to Choose the Number of Clusters__en.srt
007 How to Choose the Number of Clusters - Exercise.html
008 Pros and Cons of K-Means Clustering.mp4
008 Pros and Cons of K-Means Clustering__en.srt
008 Pros and Cons of K-Means Clustering_en.vtt
009 To Standardize or not to Standardize.mp4
009 To Standardize or not to Standardize__en.srt
010 Relationship between Clustering and Regression.mp4
010 Relationship between Clustering and Regression__en.srt
011 Market Segmentation with Cluster Analysis (Part 1).mp4
011 Market Segmentation with Cluster Analysis (Part 1)__en.srt
012 Market Segmentation with Cluster Analysis (Part 2).mp4
012 Market Segmentation with Cluster Analysis (Part 2)__en.srt
013 How is Clustering Useful_.mp4
013 How is Clustering Useful___en.srt
014 EXERCISE_ Species Segmentation with Cluster Analysis (Part 1).html
015 EXERCISE_ Species Segmentation with Cluster Analysis (Part 2).html
15452987-Categorical.csv
15453017-Countries-exercise.csv
15453029-iris-dataset.csv
15453055-iris-dataset.csv
15453059-iris-with-answers.csv
29588934-3.01.Country-clusters.csv
29588936-Country-clusters.ipynb
29588940-Country-clusters-with-comments.ipynb
29588950-Countries-exercise.csv
29588952-A-Simple-Example-of-Clustering-Exercise.ipynb
29588954-A-Simple-Example-of-Clustering-Solution.ipynb
29588960-Categorical-data.ipynb
29588968-Categorical-data-with-comments.ipynb
29588982-Clustering-Categorical-Data-Exercise.ipynb
29588986-Clustering-Categorical-Data-Solution.ipynb
29588998-Selecting-the-number-of-clusters.ipynb
29589000-Selecting-the-number-of-clusters-with-comments.ipynb
29589006-How-to-Choose-the-Number-of-Clusters-Exercise.ipynb
29589008-How-to-Choose-the-Number-of-Clusters-Solution.ipynb
29589020-Market-segmentation-example.ipynb
29589022-Market-segmentation-example-with-comments.ipynb
29589028-3.12.Example.csv
29589036-Market-segmentation-example-Part2.ipynb
29589038-Market-segmentation-example-Part2-with-comments.ipynb
29589044-Species-Segmentation-with-Cluster-Analysis-Part-1-Exercise.ipynb
29589048-Species-Segmentation-with-Cluster-Analysis-Part-1-Solution.ipynb
29589052-Species-Segmentation-with-Cluster-Analysis-Part-2-Exercise.ipynb
29589056-Species-Segmentation-with-Cluster-Analysis-Part-2-Solution.ipynb
39 - Advanced Statistical Methods - Other Types of Clustering
001 Types of Clustering.mp4
001 Types of Clustering__en.srt
002 Dendrogram.mp4
002 Dendrogram__en.srt
003 Heatmaps.mp4
003 Heatmaps__en.srt
29589066-Heatmaps.ipynb
29589070-Heatmaps-with-comments.ipynb
29589074-Country-clusters-standardized.csv
40 - Part 6_ Mathematics
001 What is a Matrix_.mp4
001 What is a Matrix___en.srt
002 Scalars and Vectors.mp4
002 Scalars and Vectors__en.srt
003 Linear Algebra and Geometry.mp4
003 Linear Algebra and Geometry__en.srt
004 Arrays in Python - A Convenient Way To Represent Matrices.mp4
004 Arrays in Python - A Convenient Way To Represent Matrices__en.srt
005 What is a Tensor_.mp4
005 What is a Tensor___en.srt
006 Addition and Subtraction of Matrices.mp4
006 Addition and Subtraction of Matrices__en.srt
007 Errors when Adding Matrices.mp4
007 Errors when Adding Matrices__en.srt
008 Transpose of a Matrix.mp4
008 Transpose of a Matrix__en.srt
009 Dot Product.mp4
009 Dot Product__en.srt
010 Dot Product of Matrices.mp4
010 Dot Product of Matrices__en.srt
011 Why is Linear Algebra Useful_.mp4
011 Why is Linear Algebra Useful___en.srt
29589122-Scalars-Vectors-and-Matrices.ipynb
29589126-Tensors.ipynb
29589134-Adding-and-subtracting-matrices.ipynb
29589174-Errors-when-adding-scalars-vectors-and-matrices-in-Python.ipynb
29589180-Tranpose-of-a-matrix.ipynb
29589188-Dot-product.ipynb
29589194-Dot-product-Part-2.ipynb
41 - Part 7_ Deep Learning
001 What to Expect from this Part_.mp4
001 What to Expect from this Part___en.srt
42 - Deep Learning - Introduction to Neural Networks
001 Introduction to Neural Networks.mp4
001 Introduction to Neural Networks__en.srt
002 Training the Model.mp4
002 Training the Model__en.srt
003 Types of Machine Learning.mp4
003 Types of Machine Learning__en.srt
004 The Linear Model (Linear Algebraic Version).mp4
004 The Linear Model (Linear Algebraic Version)__en.srt
005 The Linear Model with Multiple Inputs.mp4
005 The Linear Model with Multiple Inputs__en.srt
006 The Linear model with Multiple Inputs and Multiple Outputs.mp4
006 The Linear model with Multiple Inputs and Multiple Outputs__en.srt
007 Graphical Representation of Simple Neural Networks.mp4
007 Graphical Representation of Simple Neural Networks__en.srt
008 What is the Objective Function_.mp4
008 What is the Objective Function___en.srt
009 Common Objective Functions_ L2-norm Loss.mp4
009 Common Objective Functions_ L2-norm Loss__en.srt
010 Common Objective Functions_ Cross-Entropy Loss.mp4
010 Common Objective Functions_ Cross-Entropy Loss__en.srt
011 Optimization Algorithm_ 1-Parameter Gradient Descent.mp4
011 Optimization Algorithm_ 1-Parameter Gradient Descent__en.srt
012 Optimization Algorithm_ n-Parameter Gradient Descent.mp4
012 Optimization Algorithm_ n-Parameter Gradient Descent__en.srt
16752952-Course-Notes-Section-2.pdf
16752958-Course-Notes-Section-2.pdf
17187788-GD-function-example.xlsx
43 - Deep Learning - How to Build a Neural Network from Scratch with NumPy
001 Basic NN Example (Part 1).mp4
001 Basic NN Example (Part 1)__en.srt
002 Basic NN Example (Part 2).mp4
002 Basic NN Example (Part 2)__en.srt
003 Basic NN Example (Part 3).mp4
003 Basic NN Example (Part 3)__en.srt
004 Basic NN Example (Part 4).mp4
004 Basic NN Example (Part 4)__en.srt
005 Basic NN Example Exercises.html
13070602-Shortcuts-for-Jupyter.pdf
29589208-Minimal-example-Part-1.ipynb
29589218-Minimal-example-Part-2.ipynb
29589230-Minimal-example-Part-3.ipynb
29589236-Minimal-example-Part-4-Complete.ipynb
29589260-Minimal-example-All-Exercises.ipynb
29589266-Minimal-example-Exercise-1-Solution.ipynb
29589272-Minimal-example-Exercise-2-Solution.ipynb
29589274-Minimal-example-Exercise-3.a.Solution.ipynb
29589278-Minimal-example-Exercise-3.b.Solution.ipynb
29589280-Minimal-example-Exercise-3.c.Solution.ipynb
29589288-Minimal-example-Exercise-3.d.Solution.ipynb
29589294-Minimal-example-Exercise-4-Solution.ipynb
29589298-Minimal-example-Exercise-5-Solution.ipynb
29589302-Minimal-example-Exercise-6.ipynb
29589304-Minimal-example-Exercise-6-Solution.ipynb
44 - Deep Learning - TensorFlow 2.0_ Introduction
001 How to Install TensorFlow 2.0.mp4
001 How to Install TensorFlow 2.0__en.srt
002 TensorFlow Outline and Comparison with Other Libraries.mp4
002 TensorFlow Outline and Comparison with Other Libraries__en.srt
002 TensorFlow Outline and Comparison with Other Libraries_en.vtt
003 TensorFlow 1 vs TensorFlow 2.mp4
003 TensorFlow 1 vs TensorFlow 2__en.srt
004 A Note on TensorFlow 2 Syntax.mp4
004 A Note on TensorFlow 2 Syntax__en.srt
005 Types of File Formats Supporting TensorFlow.mp4
005 Types of File Formats Supporting TensorFlow__en.srt
006 Outlining the Model with TensorFlow 2.mp4
006 Outlining the Model with TensorFlow 2__en.srt
007 Interpreting the Result and Extracting the Weights and Bias.mp4
007 Interpreting the Result and Extracting the Weights and Bias__en.srt
008 Customizing a TensorFlow 2 Model.mp4
008 Customizing a TensorFlow 2 Model__en.srt
009 Basic NN with TensorFlow_ Exercises.html
13070604-Shortcuts-for-Jupyter.pdf
29589774-TensorFlow-Minimal-example-Part1.ipynb
29589782-TensorFlow-Minimal-example-Part2.ipynb
29589788-TensorFlow-Minimal-example-Part3.ipynb
29589804-TensorFlow-Minimal-example-complete.ipynb
29589808-TensorFlow-Minimal-example-complete-with-comments.ipynb
29589822-TensorFlow-Minimal-example-All-exercises.ipynb
29589824-TensorFlow-Minimal-example-Exercise-1-Solution.ipynb
29589828-TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb
29589834-TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb
29589836-TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb
45 - Deep Learning - Digging Deeper into NNs_ Introducing Deep Neural Networks
001 What is a Layer_.mp4
001 What is a Layer___en.srt
002 What is a Deep Net_.mp4
002 What is a Deep Net___en.srt
003 Digging into a Deep Net.mp4
003 Digging into a Deep Net__en.srt
004 Non-Linearities and their Purpose.mp4
004 Non-Linearities and their Purpose__en.srt
005 Activation Functions.mp4
005 Activation Functions__en.srt
006 Activation Functions_ Softmax Activation.mp4
006 Activation Functions_ Softmax Activation__en.srt
007 Backpropagation.mp4
007 Backpropagation__en.srt
008 Backpropagation Picture.mp4
008 Backpropagation Picture__en.srt
009 Backpropagation - A Peek into the Mathematics of Optimization.html
13070016-Course-Notes-Section-6.pdf
13070018-Course-Notes-Section-6.pdf
21993772-Backpropagation-a-peek-into-the-Mathematics-of-Optimization.pdf
46 - Deep Learning - Overfitting
001 What is Overfitting_.mp4
001 What is Overfitting___en.srt
002 Underfitting and Overfitting for Classification.mp4
002 Underfitting and Overfitting for Classification__en.srt
003 What is Validation_.mp4
003 What is Validation___en.srt
004 Training, Validation, and Test Datasets.mp4
004 Training, Validation, and Test Datasets__en.srt
005 N-Fold Cross Validation.mp4
005 N-Fold Cross Validation__en.srt
006 Early Stopping or When to Stop Training.mp4
006 Early Stopping or When to Stop Training__en.srt
47 - Deep Learning - Initialization
001 What is Initialization_.mp4
001 What is Initialization___en.srt
002 Types of Simple Initializations.mp4
002 Types of Simple Initializations__en.srt
003 State-of-the-Art Method - (Xavier) Glorot Initialization.mp4
003 State-of-the-Art Method - (Xavier) Glorot Initialization__en.srt
48 - Deep Learning - Digging into Gradient Descent and Learning Rate Schedules
001 Stochastic Gradient Descent.mp4
001 Stochastic Gradient Descent__en.srt
002 Problems with Gradient Descent.mp4
002 Problems with Gradient Descent__en.srt
003 Momentum.mp4
003 Momentum__en.srt
004 Learning Rate Schedules, or How to Choose the Optimal Learning Rate.mp4
004 Learning Rate Schedules, or How to Choose the Optimal Learning Rate__en.srt
005 Learning Rate Schedules Visualized.mp4
005 Learning Rate Schedules Visualized__en.srt
006 Adaptive Learning Rate Schedules (AdaGrad and RMSprop ).mp4
006 Adaptive Learning Rate Schedules (AdaGrad and RMSprop )__en.srt
007 Adam (Adaptive Moment Estimation).mp4
007 Adam (Adaptive Moment Estimation)__en.srt
49 - Deep Learning - Preprocessing
001 Preprocessing Introduction.mp4
001 Preprocessing Introduction__en.srt
002 Types of Basic Preprocessing.mp4
002 Types of Basic Preprocessing__en.srt
003 Standardization.mp4
003 Standardization__en.srt
004 Preprocessing Categorical Data.mp4
004 Preprocessing Categorical Data__en.srt
005 Binary and One-Hot Encoding.mp4
005 Binary and One-Hot Encoding__en.srt
50 - Deep Learning - Classifying on the MNIST Dataset
001 MNIST_ The Dataset.mp4
001 MNIST_ The Dataset__en.srt
002 MNIST_ How to Tackle the MNIST.mp4
002 MNIST_ How to Tackle the MNIST__en.srt
003 MNIST_ Importing the Relevant Packages and Loading the Data.mp4
003 MNIST_ Importing the Relevant Packages and Loading the Data__en.srt
004 MNIST_ Preprocess the Data - Create a Validation Set and Scale It.mp4
004 MNIST_ Preprocess the Data - Create a Validation Set and Scale It__en.srt
005 MNIST_ Preprocess the Data - Scale the Test Data - Exercise.html
006 MNIST_ Preprocess the Data - Shuffle and Batch.mp4
006 MNIST_ Preprocess the Data - Shuffle and Batch__en.srt
007 MNIST_ Preprocess the Data - Shuffle and Batch - Exercise.html
008 MNIST_ Outline the Model.mp4
008 MNIST_ Outline the Model__en.srt
009 MNIST_ Select the Loss and the Optimizer.mp4
009 MNIST_ Select the Loss and the Optimizer__en.srt
010 MNIST_ Learning.mp4
010 MNIST_ Learning__en.srt
011 MNIST - Exercises.html
012 MNIST_ Testing the Model.mp4
012 MNIST_ Testing the Model__en.srt
29589868-TensorFlow-MNIST-Part1-with-comments.ipynb
29589876-TensorFlow-MNIST-Part2-with-comments.ipynb
29589878-TensorFlow-MNIST-Part3-with-comments.ipynb
29589884-TensorFlow-MNIST-Part4-with-comments.ipynb
29589888-TensorFlow-MNIST-Part5-with-comments.ipynb
29589892-TensorFlow-MNIST-Part6-with-comments.ipynb
29589896-1.TensorFlow-MNIST-Width-Solution.ipynb
29589904-2.TensorFlow-MNIST-Depth-Solution.ipynb
29589908-3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb
29589912-4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb
29589920-5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb
29589928-6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb
29589932-7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb
29589934-8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb
29589940-9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb
29589948-TensorFlow-MNIST-All-Exercises.ipynb
29589952-TensorFlow-MNIST-around-98-percent-accuracy.ipynb
29589956-TensorFlow-MNIST-complete.ipynb
29589960-TensorFlow-MNIST-complete-with-comments.ipynb
51 - Deep Learning - Business Case Example
001 Business Case_ Exploring the Dataset and Identifying Predictors.mp4
001 Business Case_ Exploring the Dataset and Identifying Predictors__en.srt
002 Business Case_ Outlining the Solution.mp4
002 Business Case_ Outlining the Solution__en.srt
003 Business Case_ Balancing the Dataset.mp4
003 Business Case_ Balancing the Dataset__en.srt
004 Business Case_ Preprocessing the Data.mp4
004 Business Case_ Preprocessing the Data__en.srt
004 Business Case_ Preprocessing the Data_en.vtt
005 Business Case_ Preprocessing the Data - Exercise.html
006 Business Case_ Load the Preprocessed Data.mp4
006 Business Case_ Load the Preprocessed Data__en.srt
007 Business Case_ Load the Preprocessed Data - Exercise.html
008 Business Case_ Learning and Interpreting the Result.mp4
008 Business Case_ Learning and Interpreting the Result__en.srt
009 Business Case_ Setting an Early Stopping Mechanism.mp4
009 Business Case_ Setting an Early Stopping Mechanism__en.srt
010 Setting an Early Stopping Mechanism - Exercise.html
011 Business Case_ Testing the Model.mp4
011 Business Case_ Testing the Model__en.srt
012 Business Case_ Final Exercise.html
19664156-Audiobooks-data.csv
29589970-TensorFlow-Audiobooks-Preprocessing.ipynb
29589978-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb
29589984-TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb
29589992-TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb
29590000-TensorFlow-Audiobooks-Machine-Learning-Part1-with-comments.ipynb
29590002-TensorFlow-Audiobooks-Machine-Learning-Part2-with-comments.ipynb
29590006-TensorFlow-Audiobooks-Machine-Learning-Part3-with-comments.ipynb
29590012-TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb
29590020-TensorFlow-Audiobooks-Machine-Learning-with-comments.ipynb
52 - Deep Learning - Conclusion
001 Summary on What You've Learned.mp4
001 Summary on What You've Learned__en.srt
002 What's Further out there in terms of Machine Learning.mp4
002 What's Further out there in terms of Machine Learning__en.srt
003 DeepMind and Deep Learning.html
004 An overview of CNNs.mp4
004 An overview of CNNs__en.srt
005 An Overview of RNNs.mp4
005 An Overview of RNNs__en.srt
006 An Overview of non-NN Approaches.mp4
006 An Overview of non-NN Approaches__en.srt
53 - Appendix_ Deep Learning - TensorFlow 1_ Introduction
001 READ ME____.html
002 How to Install TensorFlow 1.mp4
002 How to Install TensorFlow 1__en.srt
002 How to Install TensorFlow 1_en.vtt
003 A Note on Installing Packages in Anaconda.html
004 TensorFlow Intro.mp4
004 TensorFlow Intro__en.srt
004 TensorFlow Intro_en.vtt
005 Actual Introduction to TensorFlow.mp4
005 Actual Introduction to TensorFlow__en.srt
006 Types of File Formats, supporting Tensors.mp4
006 Types of File Formats, supporting Tensors__en.srt
007 Basic NN Example with TF_ Inputs, Outputs, Targets, Weights, Biases.mp4
007 Basic NN Example with TF_ Inputs, Outputs, Targets, Weights, Biases__en.srt
008 Basic NN Example with TF_ Loss Function and Gradient Descent.mp4
008 Basic NN Example with TF_ Loss Function and Gradient Descent__en.srt
009 Basic NN Example with TF_ Model Output.mp4
009 Basic NN Example with TF_ Model Output__en.srt
010 Basic NN Example with TF Exercises.html
13070608-Shortcuts-for-Jupyter.pdf
29590038-5.3.TensorFlow-Minimal-example-Part-1.ipynb
29590046-5.4.TensorFlow-Minimal-example-Part-2.ipynb
29591380-5.5.TensorFlow-Minimal-example-Part-3.ipynb
29591408-5.6.TensorFlow-Minimal-example-complete.ipynb
29591428-TensorFlow-Minimal-Example-All-Exercises.ipynb
29591432-TensorFlow-Minimal-Example-Exercise-1-Solution.ipynb
29591442-TensorFlow-Minimal-Example-Exercise-2-1-Solution.ipynb
29591444-TensorFlow-Minimal-Example-Exercise-2-2-Solution.ipynb
29591454-TensorFlow-Minimal-Example-Exercise-2-3-Solution.ipynb
29591458-TensorFlow-Minimal-Example-Exercise-2-4-Solution.ipynb
29591464-TensorFlow-Minimal-Example-Exercise-3-Solution.ipynb
29591468-TensorFlow-Minimal-Example-Exercise-4-Solution.ipynb
54 - Appendix_ Deep Learning - TensorFlow 1_ Classifying on the MNIST Dataset
001 MNIST_ What is the MNIST Dataset_.mp4
001 MNIST_ What is the MNIST Dataset___en.srt
002 MNIST_ How to Tackle the MNIST.mp4
002 MNIST_ How to Tackle the MNIST__en.srt
003 MNIST_ Relevant Packages.mp4
003 MNIST_ Relevant Packages__en.srt
004 MNIST_ Model Outline.mp4
004 MNIST_ Model Outline__en.srt
005 MNIST_ Loss and Optimization Algorithm.mp4
005 MNIST_ Loss and Optimization Algorithm__en.srt
006 Calculating the Accuracy of the Model.mp4
006 Calculating the Accuracy of the Model__en.srt
007 MNIST_ Batching and Early Stopping.mp4
007 MNIST_ Batching and Early Stopping__en.srt
008 MNIST_ Learning.mp4
008 MNIST_ Learning__en.srt
009 MNIST_ Results and Testing.mp4
009 MNIST_ Results and Testing__en.srt
010 MNIST_ Exercises.html
011 MNIST_ Solutions.html
29591484-12.3.TensorFlow-MNIST-with-comments-Part-1.ipynb
29591494-12.4.TensorFlow-MNIST-with-comments-Part-2.ipynb
29591504-12.5.TensorFlow-MNIST-with-comments-Part-3.ipynb
29591514-12.6.TensorFlow-MNIST-with-comments-Part-4.ipynb
29591520-12.7.TensorFlow-MNIST-with-comments-Part-5.ipynb
29591538-12.8.TensorFlow-MNIST-with-comments-Part-6.ipynb
29591550-12.9.TensorFlow-MNIST-with-comments.ipynb
29591622-TensorFlow-MNIST-Exercises-All.ipynb
29591632-0.TensorFlow-MNIST-take-note-of-time-Solution.ipynb
29591642-1.TensorFlow-MNIST-Width-Solution.ipynb
29591650-2.TensorFlow-MNIST-Depth-Solution.ipynb
29591654-3.TensorFlow-MNIST-Width-and-Depth-Solution.ipynb
29591658-4.TensorFlow-MNIST-Activation-functions-Part-1-Solution.ipynb
29591660-5.TensorFlow-MNIST-Activation-functions-Part-2-Solution.ipynb
29591668-6.TensorFlow-MNIST-Batch-size-Part-1-Solution.ipynb
29591682-7.TensorFlow-MNIST-Batch-size-Part-2-Solution.ipynb
29591686-8.TensorFlow-MNIST-Learning-rate-Part-1-Solution.ipynb
29591690-9.TensorFlow-MNIST-Learning-rate-Part-2-Solution.ipynb
29591694-TensorFlow-MNIST-around-98-percent-accuracy.ipynb
55 - Appendix_ Deep Learning - TensorFlow 1_ Business Case
001 Business Case_ Getting Acquainted with the Dataset.mp4
001 Business Case_ Getting Acquainted with the Dataset__en.srt
002 Business Case_ Outlining the Solution.mp4
002 Business Case_ Outlining the Solution__en.srt
003 The Importance of Working with a Balanced Dataset.mp4
003 The Importance of Working with a Balanced Dataset__en.srt
004 Business Case_ Preprocessing.mp4
004 Business Case_ Preprocessing__en.srt
004 Business Case_ Preprocessing_en.vtt
005 Business Case_ Preprocessing Exercise.html
006 Creating a Data Provider.mp4
006 Creating a Data Provider__en.srt
007 Business Case_ Model Outline.mp4
007 Business Case_ Model Outline__en.srt
008 Business Case_ Optimization.mp4
008 Business Case_ Optimization__en.srt
009 Business Case_ Interpretation.mp4
009 Business Case_ Interpretation__en.srt
010 Business Case_ Testing the Model.mp4
010 Business Case_ Testing the Model__en.srt
011 Business Case_ A Comment on the Homework.mp4
011 Business Case_ A Comment on the Homework__en.srt
011 Business Case_ A Comment on the Homework_en.vtt
012 Business Case_ Final Exercise.html
13070978-Audiobooks-data.csv
29591716-Audiobooks-data.csv
29591732-Audiobooks-data.csv
29591734-TensorFlow-Audiobooks-Preprocessing.ipynb
29591738-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb
29591808-Audiobooks-data.csv
29591812-TensorFlow-Audiobooks-Machine-learning-Homework.ipynb
29591820-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb
29591842-Audiobooks-data.csv
29591844-TensorFlow-Audiobooks-Machine-learning-Homework.ipynb
29591846-TensorFlow-Audiobooks-Preprocessing-with-comments.ipynb
29591888-TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb
29591892-TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb
29591894-TensorFlow-Audiobooks-optimizing-the-algorithm.ipynb
29591900-TensorFlow-Audiobooks-optimizing-the-algorithm-with-comments.ipynb
29591906-TensorFlow-Audiobooks-Outlining-the-model.ipynb
29591910-TensorFlow-Audiobooks-Outlining-the-model-with-comments.ipynb
29591940-Audiobooks-data.csv
29591944-TensorFlow-Audiobooks-Preprocessing-Exercise.ipynb
29591948-TensorFlow-Audiobooks-Preprocessing-Exercise-Solution.ipynb
56 - Software Integration
001 What are Data, Servers, Clients, Requests, and Responses.mp4
001 What are Data, Servers, Clients, Requests, and Responses__en.srt
002 What are Data Connectivity, APIs, and Endpoints_.mp4
002 What are Data Connectivity, APIs, and Endpoints___en.srt
003 Taking a Closer Look at APIs.mp4
003 Taking a Closer Look at APIs__en.srt
004 Communication between Software Products through Text Files.mp4
004 Communication between Software Products through Text Files__en.srt
005 Software Integration - Explained.mp4
005 Software Integration - Explained__en.srt
57 - Case Study - What's Next in the Course_
001 Game Plan for this Python, SQL, and Tableau Business Exercise.mp4
001 Game Plan for this Python, SQL, and Tableau Business Exercise__en.srt
002 The Business Task.mp4
002 The Business Task__en.srt
003 Introducing the Data Set.mp4
003 Introducing the Data Set__en.srt
58 - Case Study - Preprocessing the 'Absenteeism_data'
001 What to Expect from the Following Sections_.html
002 Importing the Absenteeism Data in Python.mp4
002 Importing the Absenteeism Data in Python__en.srt
003 Checking the Content of the Data Set.mp4
003 Checking the Content of the Data Set__en.srt
004 Introduction to Terms with Multiple Meanings.mp4
004 Introduction to Terms with Multiple Meanings__en.srt
005 What's Regression Analysis - a Quick Refresher.html
006 Using a Statistical Approach towards the Solution to the Exercise.mp4
006 Using a Statistical Approach towards the Solution to the Exercise__en.srt
007 Dropping a Column from a DataFrame in Python.mp4
007 Dropping a Column from a DataFrame in Python__en.srt
008 EXERCISE - Dropping a Column from a DataFrame in Python.html
009 SOLUTION - Dropping a Column from a DataFrame in Python.html
010 Analyzing the Reasons for Absence.mp4
010 Analyzing the Reasons for Absence__en.srt
011 Obtaining Dummies from a Single Feature.mp4
011 Obtaining Dummies from a Single Feature__en.srt
012 EXERCISE - Obtaining Dummies from a Single Feature.html
013 SOLUTION - Obtaining Dummies from a Single Feature.html
014 Dropping a Dummy Variable from the Data Set.html
015 More on Dummy Variables_ A Statistical Perspective.mp4
015 More on Dummy Variables_ A Statistical Perspective__en.srt
016 Classifying the Various Reasons for Absence.mp4
016 Classifying the Various Reasons for Absence__en.srt
017 Using .concat() in Python.mp4
017 Using .concat() in Python__en.srt
018 EXERCISE - Using .concat() in Python.html
019 SOLUTION - Using .concat() in Python.html
020 Reordering Columns in a Pandas DataFrame in Python.mp4
020 Reordering Columns in a Pandas DataFrame in Python__en.srt
021 EXERCISE - Reordering Columns in a Pandas DataFrame in Python.html
022 SOLUTION - Reordering Columns in a Pandas DataFrame in Python.html
023 Creating Checkpoints while Coding in Jupyter.mp4
023 Creating Checkpoints while Coding in Jupyter__en.srt
024 EXERCISE - Creating Checkpoints while Coding in Jupyter.html
025 SOLUTION - Creating Checkpoints while Coding in Jupyter.html
026 Analyzing the Dates from the Initial Data Set.mp4
026 Analyzing the Dates from the Initial Data Set__en.srt
027 Extracting the Month Value from the _Date_ Column.mp4
027 Extracting the Month Value from the _Date_ Column__en.srt
028 Extracting the Day of the Week from the _Date_ Column.mp4
028 Extracting the Day of the Week from the _Date_ Column__en.srt
029 EXERCISE - Removing the _Date_ Column.html
030 Analyzing Several _Straightforward_ Columns for this Exercise.mp4
030 Analyzing Several _Straightforward_ Columns for this Exercise__en.srt
031 Working on _Education_, _Children_, and _Pets_.mp4
031 Working on _Education_, _Children_, and _Pets___en.srt
032 Final Remarks of this Section.mp4
032 Final Remarks of this Section__en.srt
033 A Note on Exporting Your Data as a _.csv File.html
15271310-Absenteeism-data.csv
15271322-data-preprocessing-homework.pdf
15271330-df-preprocessed.csv
29545298-Absenteeism-Exercise-Preprocessing-df-reason-mod.ipynb
29545314-Absenteeism-Exercise-Preprocessing-ChP-df-date-reason-mod.ipynb
29545316-Absenteeism-Exercise-Removing-the-Date-Column-SOLUTION.ipynb
29545318-Absenteeism-Exercise-Preprocessing-LECTURES.ipynb
29545334-Absenteeism-Exercise-Preprocessing-df-preprocessed.ipynb
29545338-Absenteeism-Exercise-EXERCISES-and-SOLUTIONS.ipynb
59 - Case Study - Applying Machine Learning to Create the 'absenteeism_module'
001 Exploring the Problem with a Machine Learning Mindset.mp4
001 Exploring the Problem with a Machine Learning Mindset__en.srt
002 Creating the Targets for the Logistic Regression.mp4
002 Creating the Targets for the Logistic Regression__en.srt
003 Selecting the Inputs for the Logistic Regression.mp4
003 Selecting the Inputs for the Logistic Regression__en.srt
004 Standardizing the Data.mp4
004 Standardizing the Data__en.srt
005 Splitting the Data for Training and Testing.mp4
005 Splitting the Data for Training and Testing__en.srt
006 Fitting the Model and Assessing its Accuracy.mp4
006 Fitting the Model and Assessing its Accuracy__en.srt
006 Fitting the Model and Assessing its Accuracy_en.vtt
007 Creating a Summary Table with the Coefficients and Intercept.mp4
007 Creating a Summary Table with the Coefficients and Intercept__en.srt
008 Interpreting the Coefficients for Our Problem.mp4
008 Interpreting the Coefficients for Our Problem__en.srt
009 Standardizing only the Numerical Variables (Creating a Custom Scaler).mp4
009 Standardizing only the Numerical Variables (Creating a Custom Scaler)__en.srt
010 Interpreting the Coefficients of the Logistic Regression.mp4
010 Interpreting the Coefficients of the Logistic Regression__en.srt
011 Backward Elimination or How to Simplify Your Model.mp4
011 Backward Elimination or How to Simplify Your Model__en.srt
011 Backward Elimination or How to Simplify Your Model_en.vtt
012 Testing the Model We Created.mp4
012 Testing the Model We Created__en.srt
013 Saving the Model and Preparing it for Deployment.mp4
013 Saving the Model and Preparing it for Deployment__en.srt
013 Saving the Model and Preparing it for Deployment_en.vtt
014 ARTICLE - A Note on 'pickling'.html
015 EXERCISE - Saving the Model (and Scaler).html
016 Preparing the Deployment of the Model through a Module.mp4
016 Preparing the Deployment of the Model through a Module__en.srt
15364076-Absenteeism-preprocessed.csv
external-assets-links.txt
60 - Case Study - Loading the 'absenteeism_module'
001 Are You Sure You're All Set_.html
002 Deploying the 'absenteeism_module' - Part I.mp4
002 Deploying the 'absenteeism_module' - Part I__en.srt
003 Deploying the 'absenteeism_module' - Part II.mp4
003 Deploying the 'absenteeism_module' - Part II__en.srt
003 Deploying the 'absenteeism_module' - Part II_en.vtt
004 Exporting the Obtained Data Set as a _.csv.html
29545348-Absenteeism-Exercise-Deploying-the-absenteeism-module.ipynb
29545372-Absenteeism-Exercise-Integration.ipynb
29545374-absenteeism-module.py
29545382-Absenteeism-new-data.csv
29545384-model
29545388-scaler
61 - Case Study - Analyzing the Predicted Outputs in Tableau
001 EXERCISE - Age vs Probability.html
002 Analyzing Age vs Probability in Tableau.mp4
002 Analyzing Age vs Probability in Tableau__en.srt
003 EXERCISE - Reasons vs Probability.html
004 Analyzing Reasons vs Probability in Tableau.mp4
004 Analyzing Reasons vs Probability in Tableau__en.srt
005 EXERCISE - Transportation Expense vs Probability.html
006 Analyzing Transportation Expense vs Probability in Tableau.mp4
006 Analyzing Transportation Expense vs Probability in Tableau__en.srt
24453624-Absenteeism-predictions.csv
29545266-Absenteeism-predictions.csv
62 - Appendix - Additional Python Tools
001 Using the .format() Method.mp4
001 Using the .format() Method__en.srt
002 Iterating Over Range Objects.mp4
002 Iterating Over Range Objects__en.srt
003 Introduction to Nested For Loops.mp4
003 Introduction to Nested For Loops__en.srt
004 Triple Nested For Loops.mp4
004 Triple Nested For Loops__en.srt
005 List Comprehensions.mp4
005 List Comprehensions__en.srt
006 Anonymous (Lambda) Functions.mp4
006 Anonymous (Lambda) Functions__en.srt
29535536-Additional-Python-Tools-Lectures.ipynb
29535540-Additional-Python-Tools-Exercises.ipynb
29535546-Additional-Python-Tools-Solutions.ipynb
29535548-Additional-Python-Tools-Lectures.ipynb
29535552-Additional-Python-Tools-Exercises.ipynb
29535554-Additional-Python-Tools-Solutions.ipynb
63 - Appendix - pandas Fundamentals
001 Introduction to pandas Series.mp4
001 Introduction to pandas Series__en.srt
002 Working with Methods in Python - Part I.mp4
002 Working with Methods in Python - Part I__en.srt
003 Working with Methods in Python - Part II.mp4
003 Working with Methods in Python - Part II__en.srt
004 Parameters and Arguments in pandas.mp4
004 Parameters and Arguments in pandas__en.srt
005 Using .unique() and .nunique().mp4
005 Using .unique() and .nunique()__en.srt
006 Using .sort_values().mp4
006 Using .sort_values()__en.srt
007 Introduction to pandas DataFrames - Part I.mp4
007 Introduction to pandas DataFrames - Part I__en.srt
008 Introduction to pandas DataFrames - Part II.mp4
008 Introduction to pandas DataFrames - Part II__en.srt
009 pandas DataFrames - Common Attributes.mp4
009 pandas DataFrames - Common Attributes__en.srt
010 Data Selection in pandas DataFrames.mp4
010 Data Selection in pandas DataFrames__en.srt
011 pandas DataFrames - Indexing with .iloc[].mp4
011 pandas DataFrames - Indexing with .iloc[]__en.srt
012 pandas DataFrames - Indexing with .loc[].mp4
012 pandas DataFrames - Indexing with .loc[]__en.srt
64 - Bonus Lecture
001 Bonus Lecture_ Next Steps.html
35215106-365-Data-Science-Data-Science-Interview-Questions-Guide.pdf
Download Paid Udemy Courses For Free.url
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