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1. Software Integration
1. Introduction to Data, Servers, Clients, Requests, and Responses.mp4
30.27 MB
2. Introduction to Data Connectivity, APIs, and Endpoints.mp4
56.20 MB
3. More on APIs.mp4
55.78 MB
4. Exchanging Information using Text Files.mp4
29.46 MB
5. Software Integration - Python-SQL-Tableau.mp4
35.37 MB
2. What_s Next in the Course_
1. What_s next in the course.mp4
25.84 MB
2. Defining the Task - Absenteeism at Work.mp4
25.54 MB
3. The Data Set.mp4
25.81 MB
3. Preprocessing the _Absenteeism_data_
1. Importing the Data Set in Python.mp4
13.03 MB
10. Concatenating Column Values.mp4
18.38 MB
11. Reordering Columns.mp4
6.94 MB
12. Creating Checkpoints in Jupyter.mp4
13.01 MB
13. Working on the _Date_ Column.mp4
26.59 MB
14. Extracting the Month Value.mp4
24.11 MB
15. Creating the _Day of the Week_ Column.mp4
15.08 MB
16. Analyzing the Next 5 Columns in our DataFrame.mp4
14.11 MB
17. Modifying _Education_ and discussing _Children_ and _Pets_.mp4
18.79 MB
18. Final Remarks on the Data Preprocessing Part of the Exercise.mp4
22.05 MB
2. Eyeballing the Data.mp4
39.36 MB
3. Introduction to Terms with Multiple Meanings.mp4
20.06 MB
4. An Analytical Approach to Solving the Task.mp4
10.93 MB
5. Dropping the _ID_ Column.mp4
34.34 MB
6. Analysis of the _Reason for Absence_ Column.mp4
20.25 MB
7. Converting a Feature into Multiple Dummy Variables.mp4
46.70 MB
8. Working with Dummy Variables from a Statistical Perspective.mp4
5.75 MB
9. Grouping the Various Reasons for Absence.mp4
38.49 MB
4. Applying Machine Learning to the Preprocessed Data
1. Exploring the Problem from a Machine Learning Point of View.mp4
25.50 MB
10. Interpreting the (Important) Coefficients.mp4
28.11 MB
11. Simplifying the Model (Backward Elimination).mp4
37.87 MB
12. Testing the Logistic Regression Model.mp4
41.45 MB
13. Saving the Logistic Regression Model.mp4
30.40 MB
14. Creating a module for later use of the model.mp4
49.61 MB
2. Creating the Targets for the Regression.mp4
34.39 MB
3. Selecting the Inputs for the Regression.mp4
12.26 MB
4. Standardizing the Dataset for Better Results.mp4
15.62 MB
5. Train-Test Split.mp4
39.92 MB
6. Training and evaluating the model.mp4
32.65 MB
7. Extracting the Intercept and Coefficients.mp4
33.39 MB
8. Interpreting the Coefficients.mp4
46.47 MB
9. Creating a Custom Scaler to Standardize Only Numerical Features.mp4
33.87 MB
5. Connecting Python and SQL
1. Loading the _absenteeism_module_.mp4
15.57 MB
10. Moving Data from Python to SQL - Part III.mp4
22.42 MB
2. Working with the _absenteeism_module_.mp4
28.36 MB
3. Creating a Database Structure in MySQL.mp4
30.34 MB
4. Installing and Importing _pymysql_.mp4
11.17 MB
5. Setting up a Connection and Creating a Cursor.mp4
10.44 MB
6. Creating the _predicted_outputs_ table in MySQL.mp4
27.40 MB
7. Executing an SQL Query from Python.mp4
12.54 MB
8. Moving Data from Python to SQL - Part I.mp4
45.36 MB
9. Moving Data from Python to SQL - Part II.mp4
32.11 MB
6. Analyzing the Obtained Data in Tableau
1. Tableau Analysis - Age vs Probability.mp4
26.42 MB
2. Tableau Analysis - Reasons vs Probability.mp4
30.18 MB
3. Tableau Analysis - Transportation Expense vs Probability.mp4
17.35 MB
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