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I. Introduction (Week 1)

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Completed 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)
Completed 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)
Completed 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)
Completed 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)

II. Linear Regression with One Variable (Week 1)

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Completed 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)
Completed 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)
Completed 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)
Completed 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)
Completed 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)
Completed 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)
Completed 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)
Completed 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)

III. Linear Algebra Review (Week 1, Optional)

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Matrices and Vectors (9 min)

Discuss for Matrices and Vectors (9 min)

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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)

IV. Linear Regression with Multiple Variables (Week 2)

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Completed 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)
Completed 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)
Completed 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)
Completed 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)
Completed 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)

V. Octave Tutorial (Week 2)

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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)

VI. Logistic Regression (Week 3)

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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)

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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)

VII. Regularization (Week 3)

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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)

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Subtitles (text) for Regularized Logistic Regression (9 min)

Subtitles (srt) for Regularized Logistic Regression (9 min)

Video (MP4) for Regularized Logistic Regression (9 min)

VIII. Neural Networks: Representation (Week 4)

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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)

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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)

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Video (MP4) for Model Representation II (12 min)
Examples and Intuitions I (7 min)

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Video (MP4) for Examples and Intuitions I (7 min)
Examples and Intuitions II (10 min)

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Video (MP4) for Examples and Intuitions II (10 min)
Multiclass Classification (4 min)

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Subtitles (text) for Multiclass Classification (4 min)

Subtitles (srt) for Multiclass Classification (4 min)

Video (MP4) for Multiclass Classification (4 min)

IX. Neural Networks: Learning (Week 5)

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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)

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Subtitles (text) for Implementation Note: Unrolling Parameters (8 min)

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Video (MP4) for Implementation Note: Unrolling Parameters (8 min)
Gradient Checking (12 min)

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Subtitles (text) for Gradient Checking (12 min)

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Video (MP4) for Gradient Checking (12 min)
Random Initialization (7 min)

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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)

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Video (MP4) for Putting It Together (14 min)
Autonomous Driving (7 min)

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Subtitles (srt) for Autonomous Driving (7 min)

Video (MP4) for Autonomous Driving (7 min)

X. Advice for Applying Machine Learning (Week 6)

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Deciding What to Try Next (6 min)

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Subtitles (text) for Deciding What to Try Next (6 min)

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Video (MP4) for Deciding What to Try Next (6 min)
Evaluating a Hypothesis (8 min)

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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)

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Video (MP4) for Model Selection and Train/Validation/Test Sets (12 min)
Diagnosing Bias vs. Variance (8 min)

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Subtitles (text) for Diagnosing Bias vs. Variance (8 min)

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Video (MP4) for Diagnosing Bias vs. Variance (8 min)
Regularization and Bias/Variance (11 min)

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Subtitles (text) for Regularization and Bias/Variance (11 min)

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Video (MP4) for Regularization and Bias/Variance (11 min)
Learning Curves (12 min)

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Subtitles (srt) for Learning Curves (12 min)

Video (MP4) for Learning Curves (12 min)
Deciding What to Do Next Revisited (7 min)

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Video (MP4) for Deciding What to Do Next Revisited (7 min)

XI. Machine Learning System Design (Week 6)

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Prioritizing What to Work On (10 min)

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Subtitles (text) for Prioritizing What to Work On (10 min)

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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)

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Video (MP4) for Error Metrics for Skewed Classes (12 min)
Trading Off Precision and Recall (14 min)

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Video (MP4) for Trading Off Precision and Recall (14 min)
Data For Machine Learning (11 min)

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Video (MP4) for Data For Machine Learning (11 min)

XII. Support Vector Machines (Week 7)

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Optimization Objective (15 min)

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Video (MP4) for Optimization Objective (15 min)
Large Margin Intuition (11 min)

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Video (MP4) for Large Margin Intuition (11 min)
Mathematics Behind Large Margin Classification (Optional) (20 min)

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Video (MP4) for Mathematics Behind Large Margin Classification (Optional) (20 min)
Kernels I (16 min)

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Kernels II (16 min)

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Video (MP4) for Kernels II (16 min)
Using An SVM (21 min)

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Video (MP4) for Using An SVM (21 min)

XIII. Clustering (Week 8)

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Unsupervised Learning: Introduction (3 min)

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Video (MP4) for Unsupervised Learning: Introduction (3 min)
K-Means Algorithm (13 min)

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Video (MP4) for K-Means Algorithm (13 min)
Optimization Objective (7 min)

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Video (MP4) for Optimization Objective (7 min)
Random Initialization (8 min)

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Video (MP4) for Random Initialization (8 min)
Choosing the Number of Clusters (8 min)

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XIV. Dimensionality Reduction (Week 8)

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Motivation I: Data Compression (10 min)

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Motivation II: Visualization (6 min)

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Video (MP4) for Motivation II: Visualization (6 min)
Principal Component Analysis Problem Formulation (9 min)

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Video (MP4) for Principal Component Analysis Problem Formulation (9 min)
Principal Component Analysis Algorithm (15 min)

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Video (MP4) for Principal Component Analysis Algorithm (15 min)
Choosing the Number of Principal Components (11 min)

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Reconstruction from Compressed Representation (4 min)

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Advice for Applying PCA (13 min)

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Video (MP4) for Advice for Applying PCA (13 min)

XV. Anomaly Detection (Week 9)

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Problem Motivation (8 min)

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Gaussian Distribution (10 min)

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Algorithm (12 min)

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Developing and Evaluating an Anomaly Detection System (13 min)

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Anomaly Detection vs. Supervised Learning (8 min)

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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)

XVI. Recommender Systems (Week 9)

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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)

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Subtitles (text) for Vectorization: Low Rank Matrix Factorization (8 min)

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Video (MP4) for Vectorization: Low Rank Matrix Factorization (8 min)
Implementational Detail: Mean Normalization (9 min)

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Subtitles (srt) for Implementational Detail: Mean Normalization (9 min)

Video (MP4) for Implementational Detail: Mean Normalization (9 min)

XVII. Large Scale Machine Learning (Week 10)

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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)

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Video (MP4) for Map Reduce and Data Parallelism (14 min)

XVIII. Application Example: Photo OCR

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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)

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Subtitles (srt) for Sliding Windows (15 min)

Video (MP4) for Sliding Windows (15 min)
Getting Lots of Data and Artificial Data (16 min)

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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)

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Video (MP4) for Ceiling Analysis: What Part of the Pipeline to Work on Next (14 min)

XIX. Conclusion

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Summary and Thank You (5 min)

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Subtitles (srt) for Summary and Thank You (5 min)

Video (MP4) for Summary and Thank You (5 min)

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