**[ Video Lectures of ML by Andrew Ng ]**

#### Video LecturesHelp Center

Having trouble viewing lectures? Try changing players. Your current player format is html5. Change to flash.

- Welcome (7 min)
Discuss for Welcome (7 min)PPT for Welcome (7 min)PDF for Welcome (7 min)Subtitles (text) for Welcome (7 min)Subtitles (srt) for Welcome (7 min)Video (MP4) for Welcome (7 min)
- What is Machine Learning? (7 min)
Discuss for What is Machine Learning? (7 min)Subtitles (text) for What is Machine Learning? (7 min)Subtitles (srt) for What is Machine Learning? (7 min)Video (MP4) for What is Machine Learning? (7 min)
- Supervised Learning (12 min)
Discuss for Supervised Learning (12 min)Subtitles (text) for Supervised Learning (12 min)Subtitles (srt) for Supervised Learning (12 min)Video (MP4) for Supervised Learning (12 min)
- Unsupervised Learning (14 min)
Discuss for Unsupervised Learning (14 min)Subtitles (text) for Unsupervised Learning (14 min)Subtitles (srt) for Unsupervised Learning (14 min)Video (MP4) for Unsupervised Learning (14 min)

- Model Representation (8 min)
Discuss for Model Representation (8 min)PPT for Model Representation (8 min)PDF for Model Representation (8 min)Subtitles (text) for Model Representation (8 min)Subtitles (srt) for Model Representation (8 min)Video (MP4) for Model Representation (8 min)
- Cost Function (8 min)
Discuss for Cost Function (8 min)Subtitles (text) for Cost Function (8 min)Subtitles (srt) for Cost Function (8 min)Video (MP4) for Cost Function (8 min)
- Cost Function – Intuition I (11 min)
Discuss for Cost Function – Intuition I (11 min)Subtitles (text) for Cost Function – Intuition I (11 min)Subtitles (srt) for Cost Function – Intuition I (11 min)Video (MP4) for Cost Function – Intuition I (11 min)
- Cost Function – Intuition II (9 min)
Discuss for Cost Function – Intuition II (9 min)Subtitles (text) for Cost Function – Intuition II (9 min)Subtitles (srt) for Cost Function – Intuition II (9 min)Video (MP4) for Cost Function – Intuition II (9 min)
- Gradient Descent (11 min)
Discuss for Gradient Descent (11 min)Subtitles (text) for Gradient Descent (11 min)Subtitles (srt) for Gradient Descent (11 min)Video (MP4) for Gradient Descent (11 min)
- Gradient Descent Intuition (12 min)
Discuss for Gradient Descent Intuition (12 min)Subtitles (text) for Gradient Descent Intuition (12 min)Subtitles (srt) for Gradient Descent Intuition (12 min)Video (MP4) for Gradient Descent Intuition (12 min)
- Gradient Descent For Linear Regression (10 min)
forum:list?forum_id=20 for Gradient Descent For Linear Regression (10 min)Subtitles (text) for Gradient Descent For Linear Regression (10 min)Subtitles (srt) for Gradient Descent For Linear Regression (10 min)Video (MP4) for Gradient Descent For Linear Regression (10 min)
- What’s Next (6 min)
Discuss for What’s Next (6 min)Subtitles (text) for What’s Next (6 min)Subtitles (srt) for What’s Next (6 min)Video (MP4) for What’s Next (6 min)

- Matrices and Vectors (9 min)
Discuss for Matrices and Vectors (9 min)PPT for Matrices and Vectors (9 min)PDF for Matrices and Vectors (9 min)Subtitles (text) for Matrices and Vectors (9 min)Subtitles (srt) for Matrices and Vectors (9 min)Video (MP4) for Matrices and Vectors (9 min)
- Addition and Scalar Multiplication (7 min)
Discuss for Addition and Scalar Multiplication (7 min)Subtitles (text) for Addition and Scalar Multiplication (7 min)Subtitles (srt) for Addition and Scalar Multiplication (7 min)Video (MP4) for Addition and Scalar Multiplication (7 min)
- Matrix Vector Multiplication (14 min)
Discuss for Matrix Vector Multiplication (14 min)Subtitles (text) for Matrix Vector Multiplication (14 min)Subtitles (srt) for Matrix Vector Multiplication (14 min)Video (MP4) for Matrix Vector Multiplication (14 min)
- Matrix Matrix Multiplication (11 min)
Discuss for Matrix Matrix Multiplication (11 min)Subtitles (text) for Matrix Matrix Multiplication (11 min)Subtitles (srt) for Matrix Matrix Multiplication (11 min)Video (MP4) for Matrix Matrix Multiplication (11 min)
- Matrix Multiplication Properties (9 min)
Discuss for Matrix Multiplication Properties (9 min)Subtitles (text) for Matrix Multiplication Properties (9 min)Subtitles (srt) for Matrix Multiplication Properties (9 min)Video (MP4) for Matrix Multiplication Properties (9 min)
- Inverse and Transpose (11 min)
Discuss for Inverse and Transpose (11 min)Subtitles (text) for Inverse and Transpose (11 min)Subtitles (srt) for Inverse and Transpose (11 min)Video (MP4) for Inverse and Transpose (11 min)

- Multiple Features (8 min)
Discuss for Multiple Features (8 min)PPT for Multiple Features (8 min)PDF for Multiple Features (8 min)Subtitles (text) for Multiple Features (8 min)Subtitles (srt) for Multiple Features (8 min)Video (MP4) for Multiple Features (8 min)
- Gradient Descent for Multiple Variables (5 min)
Discuss for Gradient Descent for Multiple Variables (5 min)Subtitles (text) for Gradient Descent for Multiple Variables (5 min)Subtitles (srt) for Gradient Descent for Multiple Variables (5 min)Video (MP4) for Gradient Descent for Multiple Variables (5 min)
- Gradient Descent in Practice I – Feature Scaling (9 min)
Discuss for Gradient Descent in Practice I – Feature Scaling (9 min)Subtitles (text) for Gradient Descent in Practice I – Feature Scaling (9 min)Subtitles (srt) for Gradient Descent in Practice I – Feature Scaling (9 min)Video (MP4) for Gradient Descent in Practice I – Feature Scaling (9 min)
- Gradient Descent in Practice II – Learning Rate (9 min)
Discuss for Gradient Descent in Practice II – Learning Rate (9 min)Subtitles (text) for Gradient Descent in Practice II – Learning Rate (9 min)Subtitles (srt) for Gradient Descent in Practice II – Learning Rate (9 min)Video (MP4) for Gradient Descent in Practice II – Learning Rate (9 min)
- Features and Polynomial Regression (8 min)
Discuss for Features and Polynomial Regression (8 min)Subtitles (text) for Features and Polynomial Regression (8 min)Subtitles (srt) for Features and Polynomial Regression (8 min)Video (MP4) for Features and Polynomial Regression (8 min)
- Normal Equation (16 min)
Discuss for Normal Equation (16 min)Subtitles (text) for Normal Equation (16 min)Subtitles (srt) for Normal Equation (16 min)Video (MP4) for Normal Equation (16 min)
- Normal Equation Noninvertibility (Optional) (6 min)
Discuss for Normal Equation Noninvertibility (Optional) (6 min)Subtitles (text) for Normal Equation Noninvertibility (Optional) (6 min)Subtitles (srt) for Normal Equation Noninvertibility (Optional) (6 min)Video (MP4) for Normal Equation Noninvertibility (Optional) (6 min)

- Basic Operations (14 min)
Discuss for Basic Operations (14 min)PPT for Basic Operations (14 min)PDF for Basic Operations (14 min)Subtitles (text) for Basic Operations (14 min)Subtitles (srt) for Basic Operations (14 min)Video (MP4) for Basic Operations (14 min)
- Moving Data Around (16 min)
Discuss for Moving Data Around (16 min)Subtitles (text) for Moving Data Around (16 min)Subtitles (srt) for Moving Data Around (16 min)Video (MP4) for Moving Data Around (16 min)
- Computing on Data (13 min)
Discuss for Computing on Data (13 min)Subtitles (text) for Computing on Data (13 min)Subtitles (srt) for Computing on Data (13 min)Video (MP4) for Computing on Data (13 min)
- Plotting Data (10 min)
Discuss for Plotting Data (10 min)Subtitles (text) for Plotting Data (10 min)Subtitles (srt) for Plotting Data (10 min)Video (MP4) for Plotting Data (10 min)
- Control Statements: for, while, if statements (13 min)
Discuss for Control Statements: for, while, if statements (13 min)Subtitles (text) for Control Statements: for, while, if statements (13 min)Subtitles (srt) for Control Statements: for, while, if statements (13 min)Video (MP4) for Control Statements: for, while, if statements (13 min)
- Vectorization (14 min)
Discuss for Vectorization (14 min)Subtitles (text) for Vectorization (14 min)Subtitles (srt) for Vectorization (14 min)Video (MP4) for Vectorization (14 min)
- Working on and Submitting Programming Exercises (4 min)
Discuss for Working on and Submitting Programming Exercises (4 min)Subtitles (text) for Working on and Submitting Programming Exercises (4 min)Subtitles (srt) for Working on and Submitting Programming Exercises (4 min)Video (MP4) for Working on and Submitting Programming Exercises (4 min)

- Classification (8 min)
Discuss for Classification (8 min)PPT for Classification (8 min)PDF for Classification (8 min)Subtitles (text) for Classification (8 min)Subtitles (srt) for Classification (8 min)Video (MP4) for Classification (8 min)
- Hypothesis Representation (7 min)
Discuss for Hypothesis Representation (7 min)Subtitles (text) for Hypothesis Representation (7 min)Subtitles (srt) for Hypothesis Representation (7 min)Video (MP4) for Hypothesis Representation (7 min)
- Decision Boundary (15 min)
Discuss for Decision Boundary (15 min)Subtitles (text) for Decision Boundary (15 min)Subtitles (srt) for Decision Boundary (15 min)Video (MP4) for Decision Boundary (15 min)
- Cost Function (11 min)
Discuss for Cost Function (11 min)Subtitles (text) for Cost Function (11 min)Subtitles (srt) for Cost Function (11 min)Video (MP4) for Cost Function (11 min)
- Simplified Cost Function and Gradient Descent (10 min)
Discuss for Simplified Cost Function and Gradient Descent (10 min)Subtitles (text) for Simplified Cost Function and Gradient Descent (10 min)Subtitles (srt) for Simplified Cost Function and Gradient Descent (10 min)Video (MP4) for Simplified Cost Function and Gradient Descent (10 min)
- Advanced Optimization (14 min)
Discuss for Advanced Optimization (14 min)Subtitles (text) for Advanced Optimization (14 min)Subtitles (srt) for Advanced Optimization (14 min)Video (MP4) for Advanced Optimization (14 min)
- Multiclass Classification: One-vs-all (6 min)
Discuss for Multiclass Classification: One-vs-all (6 min)Subtitles (text) for Multiclass Classification: One-vs-all (6 min)Subtitles (srt) for Multiclass Classification: One-vs-all (6 min)Video (MP4) for Multiclass Classification: One-vs-all (6 min)

- The Problem of Overfitting (10 min)
Discuss for The Problem of Overfitting (10 min)PPT for The Problem of Overfitting (10 min)PDF for The Problem of Overfitting (10 min)Subtitles (text) for The Problem of Overfitting (10 min)Subtitles (srt) for The Problem of Overfitting (10 min)Video (MP4) for The Problem of Overfitting (10 min)
- Cost Function (10 min)
Discuss for Cost Function (10 min)Subtitles (text) for Cost Function (10 min)Subtitles (srt) for Cost Function (10 min)Video (MP4) for Cost Function (10 min)
- Regularized Linear Regression (11 min)
Discuss for Regularized Linear Regression (11 min)Subtitles (text) for Regularized Linear Regression (11 min)Subtitles (srt) for Regularized Linear Regression (11 min)Video (MP4) for Regularized Linear Regression (11 min)
- Regularized Logistic Regression (9 min)
Discuss for Regularized Logistic Regression (9 min)Subtitles (text) for Regularized Logistic Regression (9 min)Subtitles (srt) for Regularized Logistic Regression (9 min)Video (MP4) for Regularized Logistic Regression (9 min)

- Non-linear Hypotheses (10 min)
Discuss for Non-linear Hypotheses (10 min)PPT for Non-linear Hypotheses (10 min)PDF for Non-linear Hypotheses (10 min)Subtitles (text) for Non-linear Hypotheses (10 min)Subtitles (srt) for Non-linear Hypotheses (10 min)Video (MP4) for Non-linear Hypotheses (10 min)
- Neurons and the Brain (8 min)
Discuss for Neurons and the Brain (8 min)Subtitles (text) for Neurons and the Brain (8 min)Subtitles (srt) for Neurons and the Brain (8 min)Video (MP4) for Neurons and the Brain (8 min)
- Model Representation I (12 min)
Discuss for Model Representation I (12 min)Subtitles (text) for Model Representation I (12 min)Subtitles (srt) for Model Representation I (12 min)Video (MP4) for Model Representation I (12 min)
- Model Representation II (12 min)
Discuss for Model Representation II (12 min)Subtitles (text) for Model Representation II (12 min)Subtitles (srt) for Model Representation II (12 min)Video (MP4) for Model Representation II (12 min)
- Examples and Intuitions I (7 min)
Discuss for Examples and Intuitions I (7 min)Subtitles (text) for Examples and Intuitions I (7 min)Subtitles (srt) for Examples and Intuitions I (7 min)Video (MP4) for Examples and Intuitions I (7 min)
- Examples and Intuitions II (10 min)
Discuss for Examples and Intuitions II (10 min)Subtitles (text) for Examples and Intuitions II (10 min)Subtitles (srt) for Examples and Intuitions II (10 min)Video (MP4) for Examples and Intuitions II (10 min)
- Multiclass Classification (4 min)
Discuss for Multiclass Classification (4 min)Subtitles (text) for Multiclass Classification (4 min)Subtitles (srt) for Multiclass Classification (4 min)Video (MP4) for Multiclass Classification (4 min)

- Cost Function (7 min)
Discuss for Cost Function (7 min)PPT for Cost Function (7 min)PDF for Cost Function (7 min)Subtitles (text) for Cost Function (7 min)Subtitles (srt) for Cost Function (7 min)Video (MP4) for Cost Function (7 min)
- Backpropagation Algorithm (12 min)
Discuss for Backpropagation Algorithm (12 min)Subtitles (text) for Backpropagation Algorithm (12 min)Subtitles (srt) for Backpropagation Algorithm (12 min)Video (MP4) for Backpropagation Algorithm (12 min)
- Backpropagation Intuition (13 min)
Discuss for Backpropagation Intuition (13 min)Subtitles (text) for Backpropagation Intuition (13 min)Subtitles (srt) for Backpropagation Intuition (13 min)Video (MP4) for Backpropagation Intuition (13 min)
- Implementation Note: Unrolling Parameters (8 min)
Discuss for Implementation Note: Unrolling Parameters (8 min)Subtitles (text) for Implementation Note: Unrolling Parameters (8 min)Subtitles (srt) for Implementation Note: Unrolling Parameters (8 min)Video (MP4) for Implementation Note: Unrolling Parameters (8 min)
- Gradient Checking (12 min)
Discuss for Gradient Checking (12 min)Subtitles (text) for Gradient Checking (12 min)Subtitles (srt) for Gradient Checking (12 min)Video (MP4) for Gradient Checking (12 min)
- Random Initialization (7 min)
Discuss for Random Initialization (7 min)Subtitles (text) for Random Initialization (7 min)Subtitles (srt) for Random Initialization (7 min)Video (MP4) for Random Initialization (7 min)
- Putting It Together (14 min)
Discuss for Putting It Together (14 min)Subtitles (text) for Putting It Together (14 min)Subtitles (srt) for Putting It Together (14 min)Video (MP4) for Putting It Together (14 min)
- Autonomous Driving (7 min)
Discuss for Autonomous Driving (7 min)Subtitles (text) for Autonomous Driving (7 min)Subtitles (srt) for Autonomous Driving (7 min)Video (MP4) for Autonomous Driving (7 min)

- Deciding What to Try Next (6 min)
Discuss for Deciding What to Try Next (6 min)PPT for Deciding What to Try Next (6 min)PDF for Deciding What to Try Next (6 min)Subtitles (text) for Deciding What to Try Next (6 min)Subtitles (srt) for Deciding What to Try Next (6 min)Video (MP4) for Deciding What to Try Next (6 min)
- Evaluating a Hypothesis (8 min)
Discuss for Evaluating a Hypothesis (8 min)Subtitles (text) for Evaluating a Hypothesis (8 min)Subtitles (srt) for Evaluating a Hypothesis (8 min)Video (MP4) for Evaluating a Hypothesis (8 min)
- Model Selection and Train/Validation/Test Sets (12 min)
Discuss for Model Selection and Train/Validation/Test Sets (12 min)Subtitles (text) for Model Selection and Train/Validation/Test Sets (12 min)Subtitles (srt) for Model Selection and Train/Validation/Test Sets (12 min)Video (MP4) for Model Selection and Train/Validation/Test Sets (12 min)
- Diagnosing Bias vs. Variance (8 min)
Discuss for Diagnosing Bias vs. Variance (8 min)Subtitles (text) for Diagnosing Bias vs. Variance (8 min)Subtitles (srt) for Diagnosing Bias vs. Variance (8 min)Video (MP4) for Diagnosing Bias vs. Variance (8 min)
- Regularization and Bias/Variance (11 min)
Discuss for Regularization and Bias/Variance (11 min)Subtitles (text) for Regularization and Bias/Variance (11 min)Subtitles (srt) for Regularization and Bias/Variance (11 min)Video (MP4) for Regularization and Bias/Variance (11 min)
- Learning Curves (12 min)
Discuss for Learning Curves (12 min)Subtitles (text) for Learning Curves (12 min)Subtitles (srt) for Learning Curves (12 min)Video (MP4) for Learning Curves (12 min)
- Deciding What to Do Next Revisited (7 min)
Discuss for Deciding What to Do Next Revisited (7 min)Subtitles (text) for Deciding What to Do Next Revisited (7 min)Subtitles (srt) for Deciding What to Do Next Revisited (7 min)Video (MP4) for Deciding What to Do Next Revisited (7 min)

- Prioritizing What to Work On (10 min)
Discuss for Prioritizing What to Work On (10 min)PPT for Prioritizing What to Work On (10 min)PDF for Prioritizing What to Work On (10 min)Subtitles (text) for Prioritizing What to Work On (10 min)Subtitles (srt) for Prioritizing What to Work On (10 min)Video (MP4) for Prioritizing What to Work On (10 min)
- Error Analysis (13 min)
Discuss for Error Analysis (13 min)Subtitles (text) for Error Analysis (13 min)Subtitles (srt) for Error Analysis (13 min)Video (MP4) for Error Analysis (13 min)
- Error Metrics for Skewed Classes (12 min)
Discuss for Error Metrics for Skewed Classes (12 min)Subtitles (text) for Error Metrics for Skewed Classes (12 min)Subtitles (srt) for Error Metrics for Skewed Classes (12 min)Video (MP4) for Error Metrics for Skewed Classes (12 min)
- Trading Off Precision and Recall (14 min)
Discuss for Trading Off Precision and Recall (14 min)Subtitles (text) for Trading Off Precision and Recall (14 min)Subtitles (srt) for Trading Off Precision and Recall (14 min)Video (MP4) for Trading Off Precision and Recall (14 min)
- Data For Machine Learning (11 min)
Discuss for Data For Machine Learning (11 min)Subtitles (text) for Data For Machine Learning (11 min)Subtitles (srt) for Data For Machine Learning (11 min)Video (MP4) for Data For Machine Learning (11 min)

- Optimization Objective (15 min)
Discuss for Optimization Objective (15 min)PPT for Optimization Objective (15 min)PDF for Optimization Objective (15 min)Subtitles (text) for Optimization Objective (15 min)Subtitles (srt) for Optimization Objective (15 min)Video (MP4) for Optimization Objective (15 min)
- Large Margin Intuition (11 min)
Discuss for Large Margin Intuition (11 min)Subtitles (text) for Large Margin Intuition (11 min)Subtitles (srt) for Large Margin Intuition (11 min)Video (MP4) for Large Margin Intuition (11 min)
- Mathematics Behind Large Margin Classification (Optional) (20 min)
Discuss for Mathematics Behind Large Margin Classification (Optional) (20 min)Subtitles (text) for Mathematics Behind Large Margin Classification (Optional) (20 min)Subtitles (srt) for Mathematics Behind Large Margin Classification (Optional) (20 min)Video (MP4) for Mathematics Behind Large Margin Classification (Optional) (20 min)
- Kernels I (16 min)
Discuss for Kernels I (16 min)Subtitles (text) for Kernels I (16 min)Subtitles (srt) for Kernels I (16 min)Video (MP4) for Kernels I (16 min)
- Kernels II (16 min)
Discuss for Kernels II (16 min)Subtitles (text) for Kernels II (16 min)Subtitles (srt) for Kernels II (16 min)Video (MP4) for Kernels II (16 min)
- Using An SVM (21 min)
Discuss for Using An SVM (21 min)Subtitles (text) for Using An SVM (21 min)Subtitles (srt) for Using An SVM (21 min)Video (MP4) for Using An SVM (21 min)

- Unsupervised Learning: Introduction (3 min)
Discuss for Unsupervised Learning: Introduction (3 min)PPT for Unsupervised Learning: Introduction (3 min)PDF for Unsupervised Learning: Introduction (3 min)Subtitles (text) for Unsupervised Learning: Introduction (3 min)Subtitles (srt) for Unsupervised Learning: Introduction (3 min)Video (MP4) for Unsupervised Learning: Introduction (3 min)
- K-Means Algorithm (13 min)
Discuss for K-Means Algorithm (13 min)Subtitles (text) for K-Means Algorithm (13 min)Subtitles (srt) for K-Means Algorithm (13 min)Video (MP4) for K-Means Algorithm (13 min)
- Optimization Objective (7 min)
Discuss for Optimization Objective (7 min)Subtitles (text) for Optimization Objective (7 min)Subtitles (srt) for Optimization Objective (7 min)Video (MP4) for Optimization Objective (7 min)
- Random Initialization (8 min)
Discuss for Random Initialization (8 min)Subtitles (text) for Random Initialization (8 min)Subtitles (srt) for Random Initialization (8 min)Video (MP4) for Random Initialization (8 min)
- Choosing the Number of Clusters (8 min)
Discuss for Choosing the Number of Clusters (8 min)Subtitles (text) for Choosing the Number of Clusters (8 min)Subtitles (srt) for Choosing the Number of Clusters (8 min)Video (MP4) for Choosing the Number of Clusters (8 min)

- Motivation I: Data Compression (10 min)
Discuss for Motivation I: Data Compression (10 min)PPT for Motivation I: Data Compression (10 min)PDF for Motivation I: Data Compression (10 min)Subtitles (text) for Motivation I: Data Compression (10 min)Subtitles (srt) for Motivation I: Data Compression (10 min)Video (MP4) for Motivation I: Data Compression (10 min)
- Motivation II: Visualization (6 min)
Discuss for Motivation II: Visualization (6 min)Subtitles (text) for Motivation II: Visualization (6 min)Subtitles (srt) for Motivation II: Visualization (6 min)Video (MP4) for Motivation II: Visualization (6 min)
- Principal Component Analysis Problem Formulation (9 min)
Discuss for Principal Component Analysis Problem Formulation (9 min)Subtitles (text) for Principal Component Analysis Problem Formulation (9 min)Subtitles (srt) for Principal Component Analysis Problem Formulation (9 min)Video (MP4) for Principal Component Analysis Problem Formulation (9 min)
- Principal Component Analysis Algorithm (15 min)
Discuss for Principal Component Analysis Algorithm (15 min)Subtitles (text) for Principal Component Analysis Algorithm (15 min)Subtitles (srt) for Principal Component Analysis Algorithm (15 min)Video (MP4) for Principal Component Analysis Algorithm (15 min)
- Choosing the Number of Principal Components (11 min)
Discuss for Choosing the Number of Principal Components (11 min)Subtitles (text) for Choosing the Number of Principal Components (11 min)Subtitles (srt) for Choosing the Number of Principal Components (11 min)Video (MP4) for Choosing the Number of Principal Components (11 min)
- Reconstruction from Compressed Representation (4 min)
Discuss for Reconstruction from Compressed Representation (4 min)Subtitles (text) for Reconstruction from Compressed Representation (4 min)Subtitles (srt) for Reconstruction from Compressed Representation (4 min)Video (MP4) for Reconstruction from Compressed Representation (4 min)
- Advice for Applying PCA (13 min)
Discuss for Advice for Applying PCA (13 min)Subtitles (text) for Advice for Applying PCA (13 min)Subtitles (srt) for Advice for Applying PCA (13 min)Video (MP4) for Advice for Applying PCA (13 min)

- Problem Motivation (8 min)
Discuss for Problem Motivation (8 min)PPT for Problem Motivation (8 min)PDF for Problem Motivation (8 min)Subtitles (text) for Problem Motivation (8 min)Subtitles (srt) for Problem Motivation (8 min)Video (MP4) for Problem Motivation (8 min)
- Gaussian Distribution (10 min)
Discuss for Gaussian Distribution (10 min)Subtitles (text) for Gaussian Distribution (10 min)Subtitles (srt) for Gaussian Distribution (10 min)Video (MP4) for Gaussian Distribution (10 min)
- Algorithm (12 min)
Discuss for Algorithm (12 min)Subtitles (text) for Algorithm (12 min)Subtitles (srt) for Algorithm (12 min)Video (MP4) for Algorithm (12 min)
- Developing and Evaluating an Anomaly Detection System (13 min)
Discuss for Developing and Evaluating an Anomaly Detection System (13 min)Subtitles (text) for Developing and Evaluating an Anomaly Detection System (13 min)Subtitles (srt) for Developing and Evaluating an Anomaly Detection System (13 min)Video (MP4) for Developing and Evaluating an Anomaly Detection System (13 min)
- Anomaly Detection vs. Supervised Learning (8 min)
Discuss for Anomaly Detection vs. Supervised Learning (8 min)Subtitles (text) for Anomaly Detection vs. Supervised Learning (8 min)Subtitles (srt) for Anomaly Detection vs. Supervised Learning (8 min)Video (MP4) for Anomaly Detection vs. Supervised Learning (8 min)
- Choosing What Features to Use (12 min)
Discuss for Choosing What Features to Use (12 min)Subtitles (text) for Choosing What Features to Use (12 min)Subtitles (srt) for Choosing What Features to Use (12 min)Video (MP4) for Choosing What Features to Use (12 min)
- Multivariate Gaussian Distribution (Optional) (14 min)
Discuss for Multivariate Gaussian Distribution (Optional) (14 min)Subtitles (text) for Multivariate Gaussian Distribution (Optional) (14 min)Subtitles (srt) for Multivariate Gaussian Distribution (Optional) (14 min)Video (MP4) for Multivariate Gaussian Distribution (Optional) (14 min)
- Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)
Discuss for Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)Subtitles (text) for Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)Subtitles (srt) for Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)Video (MP4) for Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min)

- Problem Formulation (8 min)
Discuss for Problem Formulation (8 min)PPT for Problem Formulation (8 min)PDF for Problem Formulation (8 min)Subtitles (text) for Problem Formulation (8 min)Subtitles (srt) for Problem Formulation (8 min)Video (MP4) for Problem Formulation (8 min)
- Content Based Recommendations (15 min)
Discuss for Content Based Recommendations (15 min)Subtitles (text) for Content Based Recommendations (15 min)Subtitles (srt) for Content Based Recommendations (15 min)Video (MP4) for Content Based Recommendations (15 min)
- Collaborative Filtering (10 min)
Discuss for Collaborative Filtering (10 min)Subtitles (text) for Collaborative Filtering (10 min)Subtitles (srt) for Collaborative Filtering (10 min)Video (MP4) for Collaborative Filtering (10 min)
- Collaborative Filtering Algorithm (9 min)
Discuss for Collaborative Filtering Algorithm (9 min)Subtitles (text) for Collaborative Filtering Algorithm (9 min)Subtitles (srt) for Collaborative Filtering Algorithm (9 min)Video (MP4) for Collaborative Filtering Algorithm (9 min)
- Vectorization: Low Rank Matrix Factorization (8 min)
Discuss for Vectorization: Low Rank Matrix Factorization (8 min)Subtitles (text) for Vectorization: Low Rank Matrix Factorization (8 min)Subtitles (srt) for Vectorization: Low Rank Matrix Factorization (8 min)Video (MP4) for Vectorization: Low Rank Matrix Factorization (8 min)
- Implementational Detail: Mean Normalization (9 min)
Discuss for Implementational Detail: Mean Normalization (9 min)Subtitles (text) for Implementational Detail: Mean Normalization (9 min)Subtitles (srt) for Implementational Detail: Mean Normalization (9 min)Video (MP4) for Implementational Detail: Mean Normalization (9 min)

- Learning With Large Datasets (6 min)
Discuss for Learning With Large Datasets (6 min)PPT for Learning With Large Datasets (6 min)PDF for Learning With Large Datasets (6 min)Subtitles (text) for Learning With Large Datasets (6 min)Subtitles (srt) for Learning With Large Datasets (6 min)Video (MP4) for Learning With Large Datasets (6 min)
- Stochastic Gradient Descent (13 min)
Discuss for Stochastic Gradient Descent (13 min)Subtitles (text) for Stochastic Gradient Descent (13 min)Subtitles (srt) for Stochastic Gradient Descent (13 min)Video (MP4) for Stochastic Gradient Descent (13 min)
- Mini-Batch Gradient Descent (6 min)
Discuss for Mini-Batch Gradient Descent (6 min)Subtitles (text) for Mini-Batch Gradient Descent (6 min)Subtitles (srt) for Mini-Batch Gradient Descent (6 min)Video (MP4) for Mini-Batch Gradient Descent (6 min)
- Stochastic Gradient Descent Convergence (12 min)
Discuss for Stochastic Gradient Descent Convergence (12 min)Subtitles (text) for Stochastic Gradient Descent Convergence (12 min)Subtitles (srt) for Stochastic Gradient Descent Convergence (12 min)Video (MP4) for Stochastic Gradient Descent Convergence (12 min)
- Online Learning (13 min)
Discuss for Online Learning (13 min)Subtitles (text) for Online Learning (13 min)Subtitles (srt) for Online Learning (13 min)Video (MP4) for Online Learning (13 min)
- Map Reduce and Data Parallelism (14 min)
Discuss for Map Reduce and Data Parallelism (14 min)Subtitles (text) for Map Reduce and Data Parallelism (14 min)Subtitles (srt) for Map Reduce and Data Parallelism (14 min)Video (MP4) for Map Reduce and Data Parallelism (14 min)

- Problem Description and Pipeline (7 min)
Discuss for Problem Description and Pipeline (7 min)PPT for Problem Description and Pipeline (7 min)PDF for Problem Description and Pipeline (7 min)Subtitles (text) for Problem Description and Pipeline (7 min)Subtitles (srt) for Problem Description and Pipeline (7 min)Video (MP4) for Problem Description and Pipeline (7 min)
- Sliding Windows (15 min)
Discuss for Sliding Windows (15 min)Subtitles (text) for Sliding Windows (15 min)Subtitles (srt) for Sliding Windows (15 min)Video (MP4) for Sliding Windows (15 min)
- Getting Lots of Data and Artificial Data (16 min)
Discuss for Getting Lots of Data and Artificial Data (16 min)Subtitles (text) for Getting Lots of Data and Artificial Data (16 min)Subtitles (srt) for Getting Lots of Data and Artificial Data (16 min)Video (MP4) for Getting Lots of Data and Artificial Data (16 min)
- Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)
Discuss for Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)Subtitles (text) for Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)Subtitles (srt) for Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)Video (MP4) for Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)

- Summary and Thank You (5 min)
Discuss for Summary and Thank You (5 min)Subtitles (text) for Summary and Thank You (5 min)Subtitles (srt) for Summary and Thank You (5 min)
# Wiki : Main

Welcome to the ML wiki page!

If you’ve recently solved a tough installation issue or gotten helpful advice about a review question, programming exercise, or the video lectures, please take some time to help out your fellow classmates by writing about it in the appropriate wiki page.

Feel free to create pages as needed. To see how to edit or create a page, see “Help” on the left navbar.

## Contents

[hide]

- 1 Course Information
- 2 Lecture Notes
- 3 Review Questions (Quizzes)
- 4 Programming Exercises
- 5 Installation Issues
- 6 Useful resources for further study
- 7 TA posts
- 8 Insights
- 9 Subtitles
- 10 Tips for Octave on OS X
- 11 Categories

## Course Information

This course is at an undergraduate level, likely situated in second or third year. The only major prerequisite is experience with at least one programming language. Octave and MATLAB are easily learned if you have programming experience. If not, plan to spend some extra time on the programming exercises. The course is not math-intensive, and all methods that use calculus are explained through use of “intuitions” for the non-expert.

## Lecture Notes

Different students have different learning styles, and having written notes to accompany the video lectures will be very useful to students who prefer learning by reading. Contributing to these notes will help those students, and will also help you internalize what you just learned!

An alternate set of lecture videos (from the ML-005 session) can be found here. These videos are identical to those used in the ML course (as of July 2015), including working subtitles, and have individual file names. Links to PDF and PPT slides of the lectures are also provided (via the icons to the right of each section of the course materials).

### Week 1

### Week 2

### Week 3

### Week 4

### Week 5

### Week 6

### Week 7

### Week 8

### Week 9

### Week 10

### A Summary

This is a summary of the course by a student.

As there are many concepts and formulas in the course, I decided to make a summary so as to have a convenient reference for some points and formulas. The summary is posted on my blog and I’m glad to share it with all of you.

### Andrew Ng video transcripts in pdf format

- Octave Tutorial (pdf), Andrew Ng, transcript written by Jose Soares Augusto, May 2012. Alternative (pdf) download.
- Neural Networks Classes (pdf), Andrew Ng, transcript written by Jose Soares Augusto, June 2012. Alternative (pdf) download.
- Support Vector Machines (SVM) Classes (pdf), Andrew Ng, transcript written by Jose Soares Augusto, June 2012. Alternative (pdf) download.
- K-Means clustering Classes (pdf), Andrew Ng, transcript written by Jose Soares Augusto, June 2012. Alternative (pdf) download.

### Errata

- Week 1 Errata
- Week 2 Errata
- Week 3 Errata
- Week 4 Errata
- Week 5 Errata
- Week 6 Errata
- Week 7 Errata
- Week 8 Errata
- Week 9 Errata
- Week 10 Errata

## Review Questions (Quizzes)

Stuck on a question’s wording? Without giving away the answers, help out your classmates by clarifying things on these pages.

- Introduction
- Linear Regression with One Variable
- Linear Algebra Review
- Linear Regression with Multiple Variables
- Support Vector Machines
- Octave Tutorial

## Programming Exercises

Did you figure out an installation issue, or solve a tricky part of the exercise? Tell your classmates about it here!

Note: You absolutely must use a text editor to modify the .m files (such as Notepad). Do not use a word processor (such as WordPad).

- Programming Exercise 1: Linear Regression
- Programming Exercise 2: Logistic Regression
- Programming Exercise 3: Multi-class Classification and Neural Networks
- Programming Exercise 4: Neural Networks Learning
- Programming Exercise 5: Regularized Linear Regression and Bias vs Variance
- Programming Exercise 6: Support Vector Machines
- Programming Exercise 7: K-Means Clustering and PCA
- Programming Exercise 8: Anomaly Detection and Recommender Systems

## Installation Issues

## Useful resources for further study

## TA posts

Toshiaki Takeuchi

## Insights

## Subtitles

## Tips for Octave on OS X

### Error message “unknown or ambiguous terminal type”

A) Try changing the terminal type with this command, for any of “qt”, “x11”, or “aqua”:

setenv("GNUTERM","qt")

B) You may also try this:

brew uninstall gnuplot brew install gnuplot --with-qt

… then add this to ~/.octaverc

setenv("GNUTERM","qt")

### The hist() or plot () function hangs

It’s not really hung – on some versions of Octave, the hist() function causes the font library to re-generated. This can take a minute or so the first time, then after that the plotting functions will work much faster.

### Errors when editing ex1 “plotData.m”

If you get an error like:

error: invalid character '�' (ASCII 226) near line 14, column 14

Then try to uncheck the TextEdit Preference – Smart quotes and Smart dashes; then use double quotes(“) instead of single quotes(‘)

### Try Using Vagrant and Virtualbox

If you are using OS X (and some brands of Linux), you can have a lot of trouble getting the visualizations to work natively. One solution is to turn to virtualization; you can find a vagrant file that gets an ubuntu machine configured in virtual box, along with scripts to make this feel like a native OS X app here:http://deepneural.blogspot.fr/p/welcome.html Another script can be found here, but this one is just the Vagrant file and does not have all the nice OS X scripts bundled with it. https://gist.github.com/Starefossen/9353638

You’ll additionally need virtualbox and vagrant to go down this route, which are thankfully both free. https://www.virtualbox.orghttps://www.vagrantup.com

You’ll need an X server, which you almost certainly are using in Linux already, but does not come out of the box with OS X. OS X users can get it here:http://www.xquartz.org