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[FreeCoursesOnline Me] A Cloud Guru - AWS Certified Machine Learning - Specialty 2020
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How you can help our Group!.txt
01 Introduction
001 Course Introduction.mp4
002 About The Exam.mp4
002 Exam Blueprint.pdf
003 About This Course.mp4
02 Data Collection
001 Introduction.mp4
002 Concepts.mp4
003 General Data Terminology.mp4
004 Image Net Data.txt
004 MNIST Data.txt
004 Machine Learning Data Terminology.mp4
004 Technobabble.txt
004 Turboencabulator Video.txt
005 AWS Data Stores.mp4
006 AWS Glue Classifiers.html
006 AWS Migration Tools.mp4
006 DMS Release Review.txt
006 Data Pipeline Activities.html
007 AWS Helper Tools.mp4
008 AWS reInvent 2018 Effective Data Lakes Challenges and Design Patterns.txt
008 AWS reInvent 2018 Modern Cloud Data Warehousing.txt
008 Build a Data Lake Foundation with AWS Glue and Amazon S3.txt
008 Exam Tips.mp4
008 Whitepaper - AWS Database Migration Service Best Practices.pdf
008 Whitepaper - Big Data Aanlytics Options on AWS.pdf
008 Whitepaper - Data Warehousing on AWS.pdf
008 Whitepaper - Migrating to Apache HBase on Amazon S3 on Amazon EMR.pdf
008 Whitepaper - Sizing Cloud Data Warehouses.pdf
03 Streaming Data Collection
001 Introduction.mp4
002 AWS Open Data Registry.txt
002 Concepts.mp4
002 Googles Big Query.txt
002 Kaggle.txt
002 UCI Machine Learning Repository.txt
003 AWS reInvent 2018 High Performance Data Streaming with Amazon Kinesis Best Practices.txt
003 Kinesis Data Streams Key Concepts.html
003 Kinesis Data Streams.mp4
004 Kinesis Firehose.mp4
004 Streaming ETL for Data Lakes using Amazon Kinesis Firehose.txt
004 What Is Amazon Kinesis Data Firehose.html
005 Analyze live video at scale in real time using Amazon Kinesis Video Streams and Amazon SageMaker.txt
005 Deep Dive - Amazon Kinesis Video Streams.txt
005 Kinesis Video Streams.mp4
006 Analyzing Data Streams in Real Time with Amazon Kinesis.txt
006 Create real-time clickstream sessions and run analytics with Amazon Kinesis Data Analytics AWS Glue and Amazon Athena.txt
006 Joining and Enriching Streaming Data on Amazon Kinesis.txt
006 Kinesis Data Analytics.mp4
007 Exam Tips.mp4
007 Real-Time Machine Learning Using Amazon Kinesis.txt
007 WHITEPAPER - Streaming Data Solutions on AWS with Amazon Kinesis.pdf
008 CloudFormation Template (setup data producer).txt
008 Create Subset Transformation Query.txt
008 Lambda function (add-newline-function).txt
008 PutRecord Python program.py
008 Streaming Data Collection Lab.mp4
008 httpsrandomuser.txt
04 Data Preparation
001 Introduction.mp4
002 Concepts.mp4
003 Categorical Encoding.mp4
004 Text Feature Engineering.mp4
004 tf-idf Vectorizer.html
005 Numeric Feature Engineering.mp4
005 scikit-learn MinMaxScaler (Normalization).html
005 scikit-learn StandardScaler (Standardization).html
006 Common Dataset Formats.html
006 MNIST datasets.txt
006 Other Feature Engineering.mp4
007 Handling Missing Values.mp4
008 Feature Selection.mp4
009 AWS Glue - How it works.html
009 AWS Glue Release Review.txt
009 AWS reInvent 2018 Integrate Amazon SageMaker with Apache Spark.txt
009 Getting Started with AWS Glue ETL.txt
009 Helper Tools.mp4
009 Using Apache Spark with Amazon SageMaker - AWS Online Tech Talks.txt
009 What is AWS Glue.txt
010 AWS reInvent 2018 Building Serverless Analytics Pipelines with AWS Glue.txt
010 AWS reInvent 2018 Integrate Amazon SageMaker with Apache Spark.txt
010 Build a Data Lake Foundation with AWS Glue and Amazon S3.txt
010 Building Serverless ETL Pipelines with AWS Glue.txt
010 Exam Tips.mp4
010 Whitepaper - Power Machine Learning at Scale.pdf
011 Age Groupings Query.txt
011 Data Preparation Lab.mp4
011 Gender Percentages Query.txt
011 Gender mapping pyspark code.py
011 Most Common Ages Query.txt
011 User Data (user-data).txt
05 Data Analysis and Visualization
001 Introduction.mp4
002 Concepts.mp4
002 Gapminder Tool.txt
003 Relationships.mp4
004 Comparisons.mp4
005 Distributions.mp4
006 Compositions.mp4
007 Choosing A Visualization.mp4
008 AWS reInvent 2018 Introducing ML Insights with Amazon QuickSight.txt
008 Amazon QuickSight Announces General Availability of ML Insights.txt
008 Exam Tips.mp4
008 Matplotlib Python Library.txt
009 Box Plot Jupyter Notebook (box-plot-example.txt
009 Car Dataset (car_data.txt
009 Data Analysis and Visualization Lab.mp4
009 Jupyter Notebooks.txt
009 my-manifest.json
06 Modeling
001 Introduction.mp4
002 Concepts.mp4
003 Data Preparation.mp4
004 SageMaker Modeling.mp4
005 SageMaker Training.mp4
006 Amazon Machine Learning Key Concepts.html
006 Exam Tips.mp4
006 Managing Machine Learning Projects.pdf
006 Use Your Own Algorithms with Amazon SageMaker.html
007 Jupyter Notebook (ufo-modeling-lab.txt
007 K-Means Hyperparameters Documentation.html
007 K-Means SageMaker Documentation.html
007 Modeling Lab.mp4
007 UFO Sightings Dataset (ufo_fullset.txt
07 Algorithms
001 Introduction.mp4
002 OPTIONAL - Why do we call them Algorithms.mp4
003 Concepts.mp4
004 Regression.mp4
005 Clustering.mp4
006 Classification.mp4
007 Image Analysis.mp4
008 Anomaly Detection.mp4
009 Text Analytics.mp4
010 Reinforcement Learning.mp4
011 Forecasting.mp4
012 Ensemble Learning.mp4
013 Exam Tips.mp4
013 Use Amazon SageMaker Built-in Algorithms.html
014 Algorithms Lab.mp4
014 Jupyter Notebook (ufo-algorithms-lab.txt
014 UFO Sightings Dataset (ufo_fullset.txt
08 Evaluation and Optimization
001 Introduction.mp4
002 Concepts.mp4
003 Monitoring and Analyzing Training Jobs.mp4
004 Evaluating Model Accuracy.mp4
005 Model Tuning.mp4
006 Amazon SageMaker Automatic Model Tuning Using Machine Learning for Machine Learning.txt
006 Easily monitor and visualize metrics while training models on Amazon SageMaker.txt
006 Exam Tips.mp4
006 Incremental Training in Amazon SageMaker.html
007 Evaluation and Optimization Lab.mp4
007 Hyperparameter Tuning with Amazon SageMakers Automatic Model Tuning - AWS Online Tech Talks.txt
007 Jupyter Notebook (ufo-evaluation-optimization-lab.txt
007 Linear Learner Hyperparameters.html
007 Training Dataset in recordIO Protobuf format (ufo_sightings_train_recordIO_protobuf.txt
007 Validation Dataset in recordIO Protobuf format (ufo_sightings_validation_recordIO_protobuf.txt
09 Implementation and Operations
001 Introduction.mp4
002 Concepts.mp4
003 AI Developer Services.mp4
004 Amazon SageMaker Deployments.mp4
005 Other ML Deployment Options.mp4
006 Security.mp4
007 Monitor and Evaluate.mp4
008 AWS Docs Best Practices for Deploying Models.html
008 AWS Whitepaper Power Machine Learning at Scale.pdf
008 Exam Tips.mp4
009 Call an Amazon SageMaker model endpoint using Amazon API Gateway and AWS Lambda.txt
009 Implementation and Operations Lab.mp4
009 Jupyter Notebook (ufo-implementation-operations-lab.txt
009 Lambda Function (lambda_function.py
009 Sample Request JSON (sample_request.json
009 UFO Full Dataset (ufo_fullset.txt
010 Deconstruction Lab.mp4
10 Wrap-Up
001 Good Luck.mp4
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