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11.95MB
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9.86KB
I. Introduction (Week 1)/1 - 2 - What is Machine Learning (7 min).mp4
9.35MB
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10.14KB
I. Introduction (Week 1)/1 - 3 - Supervised Learning (12 min).mp4
13.45MB
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16.82KB
I. Introduction (Week 1)/1 - 4 - Unsupervised Learning (14 min).mp4
16.66MB
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I. Introduction (Week 1)/1 - 4 - Unsupervised Learning (14 min).srt
29.06KB
I. Introduction (Week 1)/docs_slides_Lecture1.pdf
3.3MB
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4.02MB
II. Linear Regression with One Variable (Week 1)/2 - 1 - Model Representation (8 min).mp4
9MB
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9.05MB
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9.86KB
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12.24MB
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12.14KB
II. Linear Regression with One Variable (Week 1)/2 - 4 - Cost Function - Intuition II (9 min).mp4
11.36MB
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II. Linear Regression with One Variable (Week 1)/2 - 4 - Cost Function - Intuition II (9 min).srt
11.17KB
II. Linear Regression with One Variable (Week 1)/2 - 5 - Gradient Descent (11 min).mp4
13.5MB
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15.39KB
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13.03MB
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II. Linear Regression with One Variable (Week 1)/2 - 7 - Gradient Descent For Linear Regression (10 min).mp4
12.18MB
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II. Linear Regression with One Variable (Week 1)/2 - 7 - Gradient Descent For Linear Regression (10 min).srt
18.71KB
II. Linear Regression with One Variable (Week 1)/2 - 8 - What's Next (6 min).srt
8.45KB
II. Linear Regression with One Variable (Week 1)/2 - 8 - Whats Next (6 min).mp4
6.08MB
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2.88MB
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5.35MB
III. Linear Algebra Review (Week 1, Optional)/3 - 1 - Matrices and Vectors (9 min).mp4
9.56MB
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III. Linear Algebra Review (Week 1, Optional)/3 - 1 - Matrices and Vectors (9 min).srt
15.88KB
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7.08KB
III. Linear Algebra Review (Week 1, Optional)/3 - 2 - Addition and Scalar Multiplication (7 min).mp4
7.46MB
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III. Linear Algebra Review (Week 1, Optional)/3 - 2 - Addition and Scalar Multiplication (7 min).srt
11.97KB
III. Linear Algebra Review (Week 1, Optional)/3 - 3 - Matrix Vector Multiplication (14 min).mp4
15MB
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III. Linear Algebra Review (Week 1, Optional)/3 - 3 - Matrix Vector Multiplication (14 min).srt
24.26KB
III. Linear Algebra Review (Week 1, Optional)/3 - 4 - Matrix Matrix Multiplication (11 min).mp4
12.59MB
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III. Linear Algebra Review (Week 1, Optional)/3 - 4 - Matrix Matrix Multiplication (11 min).srt
20.6KB
III. Linear Algebra Review (Week 1, Optional)/3 - 5 - Matrix Multiplication Properties (9 min).mp4
9.81MB
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III. Linear Algebra Review (Week 1, Optional)/3 - 5 - Matrix Multiplication Properties (9 min).srt
16.75KB
III. Linear Algebra Review (Week 1, Optional)/3 - 6 - Inverse and Transpose (11 min).mp4
12.87MB
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8.84MB
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14.55KB
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IV. Linear Regression with Multiple Variables (Week 2)/4 - 3 - Gradient Descent in Practice I - Feature Scaling (9 min).mp4
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1.7MB
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IX. Neural Networks Learning (Week 5)/9 - 1 - Cost Function (7 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 2 - Backpropagation Algorithm (12 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 3 - Backpropagation Intuition (13 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 4 - Implementation Note Unrolling Parameters (8 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 5 - Gradient Checking (12 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 6 - Random Initialization (7 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 7 - Putting It Together (14 min).mp4
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IX. Neural Networks Learning (Week 5)/9 - 8 - Autonomous Driving (7 min).mp4
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9.8KB
IX. Neural Networks Learning (Week 5)/docs_slides_Lecture9.pdf
3.37MB
IX. Neural Networks Learning (Week 5)/docs_slides_Lecture9.pptx
4.96MB
IX. Neural Networks Learning (Week 5)/ex4.zip
7.58MB
V. Octave Tutorial (Week 2)/5 - 1 - Basic Operations (14 min).mp4
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242.37KB
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407.28KB
VI. Logistic Regression (Week 3)/6 - 1 - Classification (8 min).mp4
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VI. Logistic Regression (Week 3)/6 - 2 - Hypothesis Representation (7 min).mp4
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VI. Logistic Regression (Week 3)/6 - 3 - Decision Boundary (15 min).mp4
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26.75KB
VI. Logistic Regression (Week 3)/6 - 4 - Cost Function (11 min).mp4
13.09MB
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VI. Logistic Regression (Week 3)/6 - 4 - Cost Function (11 min).srt
22.17KB
VI. Logistic Regression (Week 3)/6 - 5 - Simplified Cost Function and Gradient Descent (10 min).mp4
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VI. Logistic Regression (Week 3)/6 - 5 - Simplified Cost Function and Gradient Descent (10 min).srt
19.58KB
VI. Logistic Regression (Week 3)/6 - 6 - Advanced Optimization (14 min).mp4
18.15MB
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27.8KB
VI. Logistic Regression (Week 3)/6 - 7 - Multiclass Classification One-vs-all (6 min).mp4
6.93MB
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12.61KB
VI. Logistic Regression (Week 3)/docs_slides_Lecture6.pdf
2.12MB
VI. Logistic Regression (Week 3)/docs_slides_Lecture6.pptx
3.82MB
VII. Regularization (Week 3)/7 - 1 - The Problem of Overfitting (10 min).mp4
11.15MB
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VII. Regularization (Week 3)/7 - 1 - The Problem of Overfitting (10 min).srt
19.26KB
VII. Regularization (Week 3)/7 - 2 - Cost Function (10 min).mp4
11.63MB
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19.73KB
VII. Regularization (Week 3)/7 - 3 - Regularized Linear Regression (11 min).mp4
12MB
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VII. Regularization (Week 3)/7 - 3 - Regularized Linear Regression (11 min).srt
20.37KB
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XI. Machine Learning System Design (Week 6)/11 - 3 - Error Metrics for Skewed Classes (12 min).mp4
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XI. Machine Learning System Design (Week 6)/11 - 4 - Trading Off Precision and Recall (14 min).mp4
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XI. Machine Learning System Design (Week 6)/11 - 5 - Data For Machine Learning (11 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 1 - Optimization Objective (15 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 2 - Large Margin Intuition (11 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 3 - Mathematics Behind Large Margin Classification (Optional) (20 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 4 - Kernels I (16 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min) (1).mp4
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XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min).mp4
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XII. Support Vector Machines (Week 7)/12 - 6 - Using An SVM (21 min).mp4
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XII. Support Vector Machines (Week 7)/docs_slides_Lecture12.pdf
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XII. Support Vector Machines (Week 7)/docs_slides_Lecture12.pptx
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XII. Support Vector Machines (Week 7)/ex6.zip
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XIII. Clustering (Week 8)/13 - 1 - Unsupervised Learning Introduction (3 min).mp4
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XIII. Clustering (Week 8)/13 - 2 - K-Means Algorithm (13 min).mp4
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XIII. Clustering (Week 8)/13 - 3 - Optimization Objective (7 min).mp4
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XIII. Clustering (Week 8)/13 - 4 - Random Initialization (8 min).mp4
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XIII. Clustering (Week 8)/13 - 5 - Choosing the Number of Clusters (8 min).mp4
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XIII. Clustering (Week 8)/docs_slides_Lecture13.pdf
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XIV. Dimensionality Reduction (Week 8)/14 - 1 - Motivation I Data Compression (10 min).mp4
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20.14KB
XIV. Dimensionality Reduction (Week 8)/14 - 2 - Motivation II Visualization (6 min).mp4
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10.18KB
XIV. Dimensionality Reduction (Week 8)/14 - 3 - Principal Component Analysis Problem Formulation (9 min).mp4
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18.42KB
XIV. Dimensionality Reduction (Week 8)/14 - 4 - Principal Component Analysis Algorithm (15 min).mp4
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28.58KB
XIV. Dimensionality Reduction (Week 8)/14 - 5 - Choosing the Number of Principal Components (11 min).mp4
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XIV. Dimensionality Reduction (Week 8)/14 - 6 - Reconstruction from Compressed Representation (4 min).mp4
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XIX. Conclusion/19 - 1 - Summary and Thank You (5 min).mp4
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XVI. Recommender Systems (Week 9)/16 - 3 - Collaborative Filtering (10 min).mp4
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XVI. Recommender Systems (Week 9)/16 - 5 - Vectorization Low Rank Matrix Factorization (8 min).mp4
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XVII. Large Scale Machine Learning (Week 10)/17 - 1 - Learning With Large Datasets (6 min).mp4
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