Course Modules: C S-5033-999 - ML (2022S, Online)

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START HERE: Course Overview START HERE: Course Overview 1

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RESOURCES: Course Materials RESOURCES: Course Materials 2

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Technical Support Technical Support 3

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Discussion Topic

DISCUSSION A: Experiences and Expectations DISCUSSION A: Experiences and Expectations 4

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Discussion Topic

DISCUSSION B: Course Help Board DISCUSSION B: Course Help Board 5

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LECTURE 0: Start Here LECTURE 0: Start Here 6

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Module 1: Introduction to Reinforcement Learning

Module 1: Introduction to Reinforcement Learning Module 1: Introduction to Reinforcement Learning

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INTRODUCTION 1: Introduction to Reinforcement Learning INTRODUCTION 1: Introduction to Reinforcement Learning 1

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LECTURE 1: Introduction to Reinforcement Learning LECTURE 1: Introduction to Reinforcement Learning 2

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ML_Module_01.pdf ML_Module_01.pdf 3

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Module 1 Recordings Module 1 Recordings 4

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Module 2: Dynamic Programming Methods

Module 2: Dynamic Programming Methods Module 2: Dynamic Programming Methods

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INTRODUCTION 2: Dynamic Programming Method INTRODUCTION 2: Dynamic Programming Method 1

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LECTURE 2: Dynamic Programming Methods LECTURE 2: Dynamic Programming Methods 3

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ML_Module_02.pdf ML_Module_02.pdf 5

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Module 2 Recordings Module 2 Recordings 6

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Module 3: Model-Free Methods and Prediction

Module 3: Model-Free Methods and Prediction Module 3: Model-Free Methods and Prediction

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INTRODUCTION 3: Model-Free Methods and Prediction INTRODUCTION 3: Model-Free Methods and Prediction 1

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LECTURE 3: Model-Free Methods and Prediction LECTURE 3: Model-Free Methods and Prediction 2

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ML_Module_03.pdf ML_Module_03.pdf 4

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Module 3 Recordings Module 3 Recordings 5

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Module 4: Model-Free Methods and Control

Module 4: Model-Free Methods and Control Module 4: Model-Free Methods and Control

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INTRODUCTION 4: Model-Free Methods and Control INTRODUCTION 4: Model-Free Methods and Control 1

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LECTURE 4: Model-Free Methods and Control LECTURE 4: Model-Free Methods and Control 3

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ML_Module_04.pdf ML_Module_04.pdf 4

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Module 4 Recordings Module 4 Recordings 5

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Module 5: Value-Function Approximation

Module 5: Value-Function Approximation Module 5: Value-Function Approximation

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INTRODUCTION 5: Value-Function Approximation INTRODUCTION 5: Value-Function Approximation 1

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LECTURE 5: Value-Function Approximation LECTURE 5: Value-Function Approximation 3

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ML_Module_05.pdf ML_Module_05.pdf 4

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Module 5 Recordings Module 5 Recordings 5

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Module 6: Introduction to Supervised Learning

Module 6: Introduction to Supervised Learning Module 6: Introduction to Supervised Learning

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INTRODUCTION 6: Introduction to Supervised Learning INTRODUCTION 6: Introduction to Supervised Learning 1

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LECTURE 6: Introduction to Supervised Learning LECTURE 6: Introduction to Supervised Learning 3

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ML_Module_06.pdf ML_Module_06.pdf 4

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Module 6 Recordings Module 6 Recordings 5

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Module 7: Linear Models

Module 7: Linear Models Module 7: Linear Models

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INTRODUCTION 7: Linear Models INTRODUCTION 7: Linear Models 1

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LECTURE 7: Linear Models LECTURE 7: Linear Models 2

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ML_Module_07.pdf ML_Module_07.pdf 3

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Module 7 Recordings Module 7 Recordings 4

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Module 8: Regularization, Model Selection, and Model Assessment

Module 8: Regularization, Model Selection, and Model Assessment Module 8: Regularization, Model Selection, and Model Assessment

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INTRODUCTION 8: Regularization, Model Selection, and Model Assessment INTRODUCTION 8: Regularization, Model Selection, and Model Assessment 1

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LECTURE 8: Regularization, Model Selection, and Model Assessment LECTURE 8: Regularization, Model Selection, and Model Assessment 2

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ML_Module_08.pdf ML_Module_08.pdf 3

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Module 8 Recordings Module 8 Recordings 4

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Module 9: Metrics Beyond Low Risk

Module 9: Metrics Beyond Low Risk Module 9: Metrics Beyond Low Risk

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Introduction 9: Metrics Beyond Low Risk Introduction 9: Metrics Beyond Low Risk 1

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Lecture 9: Metrics Beyond Low Risk Lecture 9: Metrics Beyond Low Risk 2

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ML_Module_09.pdf ML_Module_09.pdf 3

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Module 9: Recordings Module 9: Recordings 4

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Module 10: Artificial Neural Networks

Module 10: Artificial Neural Networks Module 10: Artificial Neural Networks

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Introduction 10: Artificial Neural Networks Introduction 10: Artificial Neural Networks 1

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Lecture 10: Artificial Neural Networks Lecture 10: Artificial Neural Networks 2

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ML_Module_10.pdf ML_Module_10.pdf 3

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Module 10: Recordings Module 10: Recordings 4

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Module 11: Decision Trees

Module 11: Decision Trees Module 11: Decision Trees

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Introduction 11: Decision Trees Introduction 11: Decision Trees 1

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Lecture 11: Decision Trees Lecture 11: Decision Trees 2

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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ML_Module_11.pdf ML_Module_11.pdf 3

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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Module 11: Recordings Module 11: Recordings 4

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete

Module 12: Ensemble Learning

Module 12: Ensemble Learning Module 12: Ensemble Learning

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Introduction 12: Ensembles Introduction 12: Ensembles 1

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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Lecture 12: Ensembles Lecture 12: Ensembles 3

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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ML_Module_12.pdf ML_Module_12.pdf 5

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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Module 12: Recordings Module 12: Recordings 6

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete

Module 13 : Support Vector Machines

Module 13 : Support Vector Machines Module 13 : Support Vector Machines

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Introduction 13: Support Vector Machines Introduction 13: Support Vector Machines 1

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Lecture 13: Support Vector Machines Lecture 13: Support Vector Machines 3

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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ML_Module_13.pdf ML_Module_13.pdf 5

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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Module 13: Recordings Module 13: Recordings 6

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Module14: Unsupervised Learning

Module14: Unsupervised Learning Module14: Unsupervised Learning

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Introduction 14: Unsupervised Learning Introduction 14: Unsupervised Learning 1

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Lecture 14: Unsupervised Learning Lecture 14: Unsupervised Learning 2

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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ML_Module_14.pdf ML_Module_14.pdf 3

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete
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Module 14: Recordings Module 14: Recordings 4

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Score at least Must score at least to complete this module item Scored at least Module item has been completed by scoring at least Score at least % Must score at least % to complete this module item Scored at least % Module item has been completed by scoring at least % View Must view in order to complete this module item Viewed Module item has been viewed and is complete Mark done Must mark this module item done in order to complete Marked done Module item marked as done and is complete Contribute Must contribute to this module item to complete it Contributed Contributed to this module item and is complete Submit Must submit this module item to complete it Submitted Module item submitted and is complete