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[FreeCourseLab com] Udemy - 2019 AWS SageMaker and Machine Learning - With Python
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1. Introduction and Housekeeping (Size: 4.59 GB) (Files: 215)
1. Introduction and Housekeeping
1. Introduction.mp4
1.1 Machine Learning at AWS Introduction_WM.pdf.pdf
2. Root Account Setup and Billing Dashboard Overview.mp4
2.1 AWS HouseKeeping_WM.pdf.pdf
3. Enable Access to Billing Data for IAM Users.mp4
4. Create Users Required For the Course.mp4
5. AWS Command Line Interface Tool Setup and Summary.mp4
6. Six Advantages of Cloud Computing.mp4
6.1 2018 AWSTop6ReasonsCloudComputing.pdf.pdf
7. AWS Global Infrastructure Overview.mp4
10. 2019 SageMaker HyperParameter Tuning
1. Downloadable Resources.html
1.1 AWS SageMaker Hyperparameter Tuning.pdf.pdf
1.2 FM-Autotuning-Lab-Configuration.xlsx.xlsx
2. Introduction to Hyperparameter Tuning.mp4
3. Lab Tuning Movie Rating Factorization Machine Recommender System.mp4
4. Lab Step 2 Tuning Movie Rating Recommender System.mp4
11. AWS Machine Learning Service
1. 2019 MARCH - Important Update AWS Machine Learning Service Deprecated.html
10. Data Types supported by AWS Machine Learning.mp4
11. Linear Regression Introduction.mp4
12. Binary Classification Introduction.mp4
13. Multiclass Classification Introduction.mp4
14. Data Visualization - Linear, Log, Quadratic and More.mp4
15. Algorithm and Terminology Quiz.html
2. Python Development Environment and Boto3 Setup.mp4
3. Project Source Code and Data Setup.mp4
3.1 ProjectSetup.zip.zip
4. Lab Intro to Python Jupyter Notebook Environment, Pandas, Matplotlib.mp4
5. Lab AWS S3 Bucket Setup and Configure Security.mp4
6. Summary.mp4
7. Introduction and House Keeping Quiz.html
8. Optional Machine Learning Where To Start (Article).html
9. Machine Learning Terminology.mp4
12. Linear Regression
1. Lab Linear Model, Squared Error Loss Function, Stochastic Gradient Descent.mp4
2. Lab Linear Regression for complex shapes.mp4
3. Summary.mp4
4. Linear Regression Quiz.html
13. AWS - Linear Regression Models
1. Lab Simple Training Data.mp4
10. AWS Regression Metrics Quiz.html
2. Lab Datasource.mp4
3. Lab Train Model with default recipe.mp4
4. AWS Models Quiz.html
5. Concept - How to evaluate regression model accuracy.mp4
6. Lab Evaluate predictive quality of the trained model.mp4
7. Lab Review Default Recipe Settings Used To Train model.mp4
8. Lab Train Model With Custom Recipe and Review Performance.mp4
9. Model Performance Summary and Conclusion.mp4
14. Adding Features To Improve Model
1. Lab Quadratic Fit Training Data.mp4
2. Lab Underfitting With Linear Features.mp4
3. Lab Normal Fit With Quadratic Features.mp4
4. Summary.mp4
15. Normalization
1. Lab Impact of Features With Different Magnitude.mp4
2. Concept Normalization to smoothen magnitude differences.mp4
3. Lab Train Model With Feature Normalizaton.mp4
4. Summary.mp4
5. Underfitting and Normalization Quiz.html
16. Adding Complex Features
1. Lab Prepare Training Data.mp4
2. Lab Adding Complex Features.mp4
3. Lab Train Model With Higher Order Features.mp4
4. Lab Performance Of Model With Degree 1 Features.mp4
5. Lab Performance of Model with Degree 4 Features.mp4
6. Lab Performance of Model With Degree 15 Features.mp4
7. Summary.mp4
17. Kaggle Bike Hourly Rental Prediction
1. Review Kaggle Bike Train Problem And Dataset.mp4
2. Lab Train Model To Predict Hourly Rental.mp4
3. Lab Evaluate Prediction Quality.mp4
4. Linear Regression Wrapup and Summary.mp4
18. Logistic Regression
1. Binary Classification - Logistic Regression, Loss Function, Optimization.mp4
2. Lab Binary Classification Approach.mp4
3. True Positive, True Negative, False Positive and False Negative.mp4
4. Lab Logistic Optimization Objectives.mp4
5. Lab Logistic Cost Function.mp4
6. Lab Cost Example.mp4
7. Optimizing Weights.mp4
8. Summary.mp4
9. Logistic Regression Quiz.html
19. Onset of Diabetes Prediction
1. Problem Objective, Input Data and Strategy.mp4
10. Lab Batch Prediction and Compute Metrics.mp4
11. Summary.mp4
12. Logistic Regression Metrics Quiz.html
2. Lab Prepare For Training.mp4
3. Lab Training a Classification Model.mp4
4. Concept Classification Metrics.mp4
5. Concept Classification Insights with AWS Histograms.mp4
6. Concept AUC Metric.mp4
7. Lab Review Diabetes Model Performance.mp4
8. Lab Cutoff Threshold Interactive Testing.mp4
9. Lab Evaluating Prediction Quality With Additional Dataset.mp4
2. 2019 SageMaker Housekeeping
1. Downloadable Resources.html
1.1 SourceCode and Data Setup.pdf.pdf
1.2 AWS Introduction ML Concepts.pdf.pdf
2. Demo - S3 Bucket Setup.mp4
3. Demo - Setup SageMaker Notebook Instance.mp4
4. 2019 Demo - Source Code and Data Setup.mp4
20. Multiclass Classifiers using Multinomial Logistic Regression
1. Lab Iris Classifcation.mp4
2. Lab Train Classifier with Default and Custom Recipe.mp4
3. Concept Evaluating Predictive Quality of Multiclass Classifiers.mp4
4. Concept Confusion Matrix To Evaluating Predictive Quality.mp4
5. Lab Evaluate Performance of Iris Classifiers using Default Recipe.mp4
6. Lab Evaluate Performance of Iris Classifiers using Custom Recipe.mp4
7. Lab Batch Prediction and Computing Metrics using Python Code.mp4
8. Summary.mp4
21. Text Based Classification with AWS Twitter Dataset
1. AWS Twitter Feed Classification for Customer Service.mp4
2. Lab Train, Evaluate Model and Assess Predictive Quality.mp4
3. Lab Interactive Prediction with AWS.mp4
4. Logistic Regression Summary.mp4
22. Data Transformation using Recipes
1. Recipe Overview.mp4
2. Recipe Example.mp4
3. Text Transformation.mp4
4. Numeric Transformation - Quantile Binning.mp4
5. Numeric Transformation - Normalization.mp4
6. Cartesian Product Transformation - Categorical and Text.mp4
7. Summary.mp4
23. Hyper Parameters, Model Optimization and Lifecycle
1. Introduction.mp4
2. Data Rearrangement, Maximum Model Size, Passes, Shuffle Type.mp4
3. Regularization, Learning Rate.mp4
4. Regularization Effect.mp4
5. Improving Model Quality.mp4
6. Model Maintenance.mp4
7. AWS Machine Learning System Limits.mp4
8. AWS Machine Learning Pricing.mp4
24. Integration of AWS Machine Learning With Your Application
1. Introduction.mp4
10. Demo Allowing Prediction Only For Registered Users.mp4
11. Cognito Overview.mp4
12. Lab Cognito User Pool Configuration.mp4
13. Lab AngularJS Web Client - Invoke Prediction for authorized users.mp4
14. Lab Invoke Machine Learning Service From AWS EC2 Instance.mp4
15. Summary.mp4
2. Integration Scenarios.mp4
3. Security using IAM.mp4
4. Hands-on lab - List of Demos and Objective.mp4
5. Lab Enable Real Time End Point and Configure IAM Prediction User.mp4
6. Lab Invoking Prediction From AWS Command Line Interface.mp4
6.1 aws_ml_command_line.txt.txt
7. Lab Invoking Prediction From Python Client.mp4
8. Lab Python Client to Train, Evaluate Models and Integrate with AWS.mp4
9. Lab Invoking Prediction From Web Page AngularJS Client.mp4
25. Homework - Additional Problems
1. Mushroom Classification.html
1.1 MushroomData_Class.csv.csv
26. Conclusion
1. BONUS Learn Advanced Data Processing Techniques, Cloud Computing and More.html
2. Conclusion.mp4
3. 2019 Machine Learning Concepts
1. 2019 Introduction to Machine Learning, Concepts, Terminologies.mp4
2. 2019 Data Types - How to handle mixed data types.mp4
3. 2019 Introduction to Python Notebook Environment.mp4
4. 2019 Introduction to working with Missing Data.mp4
5. 2019 Data Visualization - Linear, Log, Quadratic and More.mp4
4. 2019 SageMaker Service Overview
1. Downloadable Resources.html
1.1 AWS SageMaker_WM.pdf.pdf
2. SageMaker Overview.mp4
3. Compute Instance Families and Pricing.mp4
4. Algorithms and Data Formats Supported For Training and Inference.mp4
5. XGBoost - Gradient Boosted Trees
1. Introduction to XGBoost.mp4
10. Demo - Training on SageMaker Cloud - Kaggle Bike Rental Model Version 3.mp4
11. Demo - Invoking SageMaker Model Endpoints For Real Time Predictions.mp4
12. Demo - Invoking SageMaker Model Endpoints From Client Outside of AWS.mp4
13. How to remove SageMaker endpoints and Shutdown Notebook Instance.html
13.1 20. How to remove SageMaker endpoints and Shutdown Notebook Instance.pdf.pdf
14. Creating EndPoint From Existing Model Artifacts.html
15. XGBoost Hyper Parameter Tuning.mp4
16. Demo - XGBoost Multi-Class Classification Iris Data.mp4
17. Demo - XGBoost Binary Classifier For Diabetes Prediction.mp4
18. Demo - XGBoost Binary Classifier for Edible Mushroom Prediction.mp4
19. Summary - XGBoost.mp4
2. Source Code Overview.mp4
3. Demo - Create Files in SageMaker Data Formats and Save Files To S3.mp4
4. Demo - Working with XGBoost - Linear Regression Straight Line Fit.mp4
5. Demo - XGBoost Example with Quadratic Fit.mp4
6. Demo - Kaggle Bike Rental Data Setup, Exploration and Preparation.mp4
7. Demo - Kaggle Bike Rental Model Version 1.mp4
8. Demo - Kaggle Bike Rental Model Version 2.mp4
9. Demo - Kaggle Bike Rental Model Version 3.mp4
6. SageMaker - Principal Component Analysis (PCA)
1. Downloadable Resources.html
1.1 AWS SageMakerPCA_WM.pdf.pdf
10. Demo - PCA Projection with SageMaker.mp4
11. Exercise Kaggle Bike Train and PCA.html
12. Summary.mp4
2. Introduction to Principal Component Analysis (PCA).mp4
3. PCA Demo Overview.mp4
4. Demo - PCA with Random Dataset.mp4
5. Demo - PCA with Correlated Dataset.mp4
6. Cleanup Resources on SageMaker.html
7. Demo - PCA with Kaggle Bike Sharing - Overview and Normalization.mp4
8. Demo - PCA Local Model with Kaggle Bike Train.mp4
9. Demo - PCA training with SageMaker.mp4
7. SageMaker - Factorization Machines
1. Downloadable Resources.html
1.1 2. AWS SageMakerFactorizationMachine_WM.pdf.pdf
2. Introduction to Factorization Machines.mp4
3. MovieLens Dataset.html
4. Demo - Movie Recommender Data Preparation.mp4
5. Demo - Movie Recommender Model Training.mp4
6. Demo - Movie Predictions By User.mp4
8. SageMaker - DeepAR Time Series Forecasting
1. Downloadable Resources.html
1.1 AWS SageMakerDeepAR_WM.pdf.pdf
10. Demo - DeepAR Dynamic Features Training and Prediction.mp4
11. Summary.mp4
2. Introduction to DeepAR Time Series Forecasting.mp4
3. DeepAR Training and Inference Formats.mp4
4. Working with Time Series Data, Handling Missing Values.mp4
5. Demo - Bike Rental as Time Series Forecasting Problem.mp4
6. Demo - Bike Rental Model Training.mp4
7. Demo - Bike Rental Prediction.mp4
8. Demo - DeepAR Categories.mp4
9. Demo - DeepAR Dynamic Features Data Preparation.mp4
9. 2019 Integration Options - Model Endpoint
1. Downloadable Resources.html
1.1 AWS SageMaker Integration.pdf.pdf
1.2 Local Machine - Housekeeping.pdf.pdf
2. Integration Overview.mp4
3. Install Python and Boto3 - Local Machine.mp4
4. Install SageMaker SDK, GIT Client, Source Code, Security Permissions.html
4.1 Local Machine - Housekeeping.pdf.pdf
5. Client to Endpoint using SageMaker SDK.mp4
6. Client to Endpoint using Boto3 SDK.mp4
7. Microservice - Lambda to Endpoint - Payload.mp4
8. Microservice - Lambda to Endpoint.mp4
9. Microservice - API Gateway, Lambda to Endpoint.mp4
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