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[Coursera] Machine Learning from Stanford Universi...
Seeders: 10 Leechers: 8
[Coursera] Machine Learning from Stanford University Torrent content (File list)
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avatar.png 55.4 KB |
I. Introduction (Week 1)/1 - 1 - Welcome (7 min).mp4 12.0 MB |
I. Introduction (Week 1)/1 - 1 - Welcome (7 min).srt 9.9 KB |
I. Introduction (Week 1)/1 - 2 - What is Machine Learning (7 min).mp4 9.4 MB |
I. Introduction (Week 1)/1 - 2 - What is Machine Learning- (7 min).srt 10.1 KB |
I. Introduction (Week 1)/1 - 3 - Supervised Learning (12 min).mp4 13.5 MB |
I. Introduction (Week 1)/1 - 3 - Supervised Learning (12 min).srt 16.8 KB |
I. Introduction (Week 1)/1 - 4 - Unsupervised Learning (14 min).mp4 16.7 MB |
I. Introduction (Week 1)/1 - 4 - Unsupervised Learning (14 min).srt 29.1 KB |
I. Introduction (Week 1)/docs_slides_Lecture1.pdf 3.3 MB |
I. Introduction (Week 1)/docs_slides_Lecture1.pptx 4.0 MB |
II. Linear Regression with One Variable (Week 1)/2 - 1 - Model Representation (8 min).mp4 9.0 MB |
II. Linear Regression with One Variable (Week 1)/2 - 1 - Model Representation (8 min).srt 9.9 KB |
II. Linear Regression with One Variable (Week 1)/2 - 2 - Cost Function (8 min).mp4 9.0 MB |
II. Linear Regression with One Variable (Week 1)/2 - 2 - Cost Function (8 min).srt 9.9 KB |
II. Linear Regression with One Variable (Week 1)/2 - 3 - Cost Function - Intuition I (11 min).mp4 12.2 MB |
II. Linear Regression with One Variable (Week 1)/2 - 3 - Cost Function - Intuition I (11 min).srt 12.1 KB |
II. Linear Regression with One Variable (Week 1)/2 - 4 - Cost Function - Intuition II (9 min).mp4 11.4 MB |
II. Linear Regression with One Variable (Week 1)/2 - 4 - Cost Function - Intuition II (9 min).srt 11.2 KB |
II. Linear Regression with One Variable (Week 1)/2 - 5 - Gradient Descent (11 min).mp4 13.5 MB |
II. Linear Regression with One Variable (Week 1)/2 - 5 - Gradient Descent (11 min).srt 15.4 KB |
II. Linear Regression with One Variable (Week 1)/2 - 6 - Gradient Descent Intuition (12 min).mp4 13.0 MB |
II. Linear Regression with One Variable (Week 1)/2 - 6 - Gradient Descent Intuition (12 min).srt 15.5 KB |
II. Linear Regression with One Variable (Week 1)/2 - 7 - Gradient Descent For Linear Regression (10 min).mp4 12.2 MB |
II. Linear Regression with One Variable (Week 1)/2 - 7 - Gradient Descent For Linear Regression (10 min).srt 18.7 KB |
II. Linear Regression with One Variable (Week 1)/2 - 8 - What's Next (6 min).srt 8.5 KB |
II. Linear Regression with One Variable (Week 1)/2 - 8 - Whats Next (6 min).mp4 6.1 MB |
II. Linear Regression with One Variable (Week 1)/docs_slides_Lecture2.pdf 2.9 MB |
II. Linear Regression with One Variable (Week 1)/docs_slides_Lecture2.pptx 5.4 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 1 - Matrices and Vectors (9 min).mp4 9.6 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 1 - Matrices and Vectors (9 min).srt 15.9 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 1 - Matrices and Vectors (9 min).txt 7.1 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 2 - Addition and Scalar Multiplication (7 min).mp4 7.5 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 2 - Addition and Scalar Multiplication (7 min).srt 12.0 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 3 - Matrix Vector Multiplication (14 min).mp4 15.0 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 3 - Matrix Vector Multiplication (14 min).srt 24.3 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 4 - Matrix Matrix Multiplication (11 min).mp4 12.6 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 4 - Matrix Matrix Multiplication (11 min).srt 20.6 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 5 - Matrix Multiplication Properties (9 min).mp4 9.8 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 5 - Matrix Multiplication Properties (9 min).srt 16.8 KB |
III. Linear Algebra Review (Week 1, Optional)/3 - 6 - Inverse and Transpose (11 min).mp4 12.9 MB |
III. Linear Algebra Review (Week 1, Optional)/3 - 6 - Inverse and Transpose (11 min).srt 21.1 KB |
III. Linear Algebra Review (Week 1, Optional)/docs_slides_Lecture3.pdf 1.8 MB |
III. Linear Algebra Review (Week 1, Optional)/docs_slides_Lecture3.pptx 4.9 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 1 - Multiple Features (8 min).mp4 8.8 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 1 - Multiple Features (8 min).srt 14.5 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 2 - Gradient Descent for Multiple Variables (5 min).mp4 5.8 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 2 - Gradient Descent for Multiple Variables (5 min).srt 6.6 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 3 - Gradient Descent in Practice I - Feature Scaling (9 min).mp4 9.5 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 3 - Gradient Descent in Practice I - Feature Scaling (9 min).srt 17.0 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 4 - Gradient Descent in Practice II - Learning Rate (9 min).mp4 9.3 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 4 - Gradient Descent in Practice II - Learning Rate (9 min).srt 18.5 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 5 - Features and Polynomial Regression (8 min).mp4 8.3 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 5 - Features and Polynomial Regression (8 min).srt 15.9 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 6 - Normal Equation (16 min).mp4 17.1 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 6 - Normal Equation (16 min).srt 31.2 KB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 7 - Normal Equation Noninvertibility (Optional) (6 min).mp4 6.2 MB |
IV. Linear Regression with Multiple Variables (Week 2)/4 - 7 - Normal Equation Noninvertibility (Optional) (6 min).srt 9.8 KB |
IV. Linear Regression with Multiple Variables (Week 2)/docs_slides_Lecture4.pdf 1.7 MB |
IV. Linear Regression with Multiple Variables (Week 2)/docs_slides_Lecture4.pptx 4.4 MB |
IV. Linear Regression with Multiple Variables (Week 2)/ex1.zip 469.8 KB |
IX. Neural Networks Learning (Week 5)/9 - 1 - Cost Function (7 min).mp4 7.7 MB |
IX. Neural Networks Learning (Week 5)/9 - 1 - Cost Function (7 min).srt 13.2 KB |
IX. Neural Networks Learning (Week 5)/9 - 2 - Backpropagation Algorithm (12 min).mp4 13.9 MB |
IX. Neural Networks Learning (Week 5)/9 - 2 - Backpropagation Algorithm (12 min).srt 22.8 KB |
IX. Neural Networks Learning (Week 5)/9 - 3 - Backpropagation Intuition (13 min).mp4 15.4 MB |
IX. Neural Networks Learning (Week 5)/9 - 3 - Backpropagation Intuition (13 min).srt 25.0 KB |
IX. Neural Networks Learning (Week 5)/9 - 4 - Implementation Note Unrolling Parameters (8 min).mp4 9.4 MB |
IX. Neural Networks Learning (Week 5)/9 - 4 - Implementation Note- Unrolling Parameters (8 min).srt 14.9 KB |
IX. Neural Networks Learning (Week 5)/9 - 5 - Gradient Checking (12 min).mp4 13.5 MB |
IX. Neural Networks Learning (Week 5)/9 - 5 - Gradient Checking (12 min).srt 23.6 KB |
IX. Neural Networks Learning (Week 5)/9 - 6 - Random Initialization (7 min).mp4 7.6 MB |
IX. Neural Networks Learning (Week 5)/9 - 6 - Random Initialization (7 min).srt 14.0 KB |
IX. Neural Networks Learning (Week 5)/9 - 7 - Putting It Together (14 min).mp4 16.3 MB |
IX. Neural Networks Learning (Week 5)/9 - 7 - Putting It Together (14 min).srt 27.7 KB |
IX. Neural Networks Learning (Week 5)/9 - 8 - Autonomous Driving (7 min).mp4 14.9 MB |
IX. Neural Networks Learning (Week 5)/9 - 8 - Autonomous Driving (7 min).srt 9.8 KB |
IX. Neural Networks Learning (Week 5)/docs_slides_Lecture9.pdf 3.4 MB |
IX. Neural Networks Learning (Week 5)/docs_slides_Lecture9.pptx 5.0 MB |
IX. Neural Networks Learning (Week 5)/ex4.zip 7.6 MB |
V. Octave Tutorial (Week 2)/5 - 1 - Basic Operations (14 min).mp4 17.7 MB |
V. Octave Tutorial (Week 2)/5 - 1 - Basic Operations (14 min).srt 25.4 KB |
V. Octave Tutorial (Week 2)/5 - 2 - Moving Data Around (16 min).mp4 20.8 MB |
V. Octave Tutorial (Week 2)/5 - 2 - Moving Data Around (16 min).srt 28.6 KB |
V. Octave Tutorial (Week 2)/5 - 3 - Computing on Data (13 min).mp4 15.3 MB |
V. Octave Tutorial (Week 2)/5 - 3 - Computing on Data (13 min).srt 24.9 KB |
V. Octave Tutorial (Week 2)/5 - 4 - Plotting Data (10 min).mp4 13.3 MB |
V. Octave Tutorial (Week 2)/5 - 4 - Plotting Data (10 min).srt 17.4 KB |
V. Octave Tutorial (Week 2)/5 - 5 - Control Statements for while if statements (13 min).mp4 16.5 MB |
V. Octave Tutorial (Week 2)/5 - 5 - Control Statements- for, while, if statements (13 min).srt 23.4 KB |
V. Octave Tutorial (Week 2)/5 - 6 - Vectorization (14 min).mp4 16.1 MB |
V. Octave Tutorial (Week 2)/5 - 6 - Vectorization (14 min).srt 25.2 KB |
V. Octave Tutorial (Week 2)/5 - 7 - Working on and Submitting Programming Exercises (4 min).mp4 5.5 MB |
V. Octave Tutorial (Week 2)/5 - 7 - Working on and Submitting Programming Exercises (4 min).srt 4.4 KB |
V. Octave Tutorial (Week 2)/docs_slides_Lecture5.pdf 242.4 KB |
V. Octave Tutorial (Week 2)/docs_slides_Lecture5.pptx 407.3 KB |
VI. Logistic Regression (Week 3)/6 - 1 - Classification (8 min).mp4 8.8 MB |
VI. Logistic Regression (Week 3)/6 - 1 - Classification (8 min).srt 16.2 KB |
VI. Logistic Regression (Week 3)/6 - 2 - Hypothesis Representation (7 min).mp4 8.3 MB |
VI. Logistic Regression (Week 3)/6 - 2 - Hypothesis Representation (7 min).srt 14.2 KB |
VI. Logistic Regression (Week 3)/6 - 3 - Decision Boundary (15 min).mp4 16.7 MB |
VI. Logistic Regression (Week 3)/6 - 3 - Decision Boundary (15 min).srt 26.7 KB |
VI. Logistic Regression (Week 3)/6 - 4 - Cost Function (11 min).mp4 13.1 MB |
VI. Logistic Regression (Week 3)/6 - 4 - Cost Function (11 min).srt 22.2 KB |
VI. Logistic Regression (Week 3)/6 - 5 - Simplified Cost Function and Gradient Descent (10 min).mp4 12.0 MB |
VI. Logistic Regression (Week 3)/6 - 5 - Simplified Cost Function and Gradient Descent (10 min).srt 19.6 KB |
VI. Logistic Regression (Week 3)/6 - 6 - Advanced Optimization (14 min).mp4 18.2 MB |
VI. Logistic Regression (Week 3)/6 - 6 - Advanced Optimization (14 min).srt 27.8 KB |
VI. Logistic Regression (Week 3)/6 - 7 - Multiclass Classification One-vs-all (6 min).mp4 6.9 MB |
VI. Logistic Regression (Week 3)/6 - 7 - Multiclass Classification- One-vs-all (6 min).srt 12.6 KB |
VI. Logistic Regression (Week 3)/docs_slides_Lecture6.pdf 2.1 MB |
VI. Logistic Regression (Week 3)/docs_slides_Lecture6.pptx 3.8 MB |
VII. Regularization (Week 3)/7 - 1 - The Problem of Overfitting (10 min).mp4 11.1 MB |
VII. Regularization (Week 3)/7 - 1 - The Problem of Overfitting (10 min).srt 19.3 KB |
VII. Regularization (Week 3)/7 - 2 - Cost Function (10 min).mp4 11.6 MB |
VII. Regularization (Week 3)/7 - 2 - Cost Function (10 min).srt 19.7 KB |
VII. Regularization (Week 3)/7 - 3 - Regularized Linear Regression (11 min).mp4 12.0 MB |
VII. Regularization (Week 3)/7 - 3 - Regularized Linear Regression (11 min).srt 20.4 KB |
VII. Regularization (Week 3)/7 - 4 - Regularized Logistic Regression (9 min).mp4 10.9 MB |
VII. Regularization (Week 3)/7 - 4 - Regularized Logistic Regression (9 min).srt 17.2 KB |
VII. Regularization (Week 3)/docs_slides_Lecture7.pdf 2.3 MB |
VII. Regularization (Week 3)/docs_slides_Lecture7.pptx 2.6 MB |
VII. Regularization (Week 3)/ex2.zip 243.0 KB |
VIII. Neural Networks Representation (Week 4)/8 - 1 - Non-linear Hypotheses (10 min).mp4 10.9 MB |
VIII. Neural Networks Representation (Week 4)/8 - 1 - Non-linear Hypotheses (10 min).srt 19.0 KB |
VIII. Neural Networks Representation (Week 4)/8 - 2 - Neurons and the Brain (8 min).mp4 9.9 MB |
VIII. Neural Networks Representation (Week 4)/8 - 2 - Neurons and the Brain (8 min).srt 16.4 KB |
VIII. Neural Networks Representation (Week 4)/8 - 3 - Model Representation I (12 min).mp4 13.5 MB |
VIII. Neural Networks Representation (Week 4)/8 - 3 - Model Representation I (12 min).srt 21.6 KB |
VIII. Neural Networks Representation (Week 4)/8 - 4 - Model Representation II (12 min).mp4 13.5 MB |
VIII. Neural Networks Representation (Week 4)/8 - 4 - Model Representation II (12 min).srt 22.4 KB |
VIII. Neural Networks Representation (Week 4)/8 - 5 - Examples and Intuitions I (7 min).mp4 7.9 MB |
VIII. Neural Networks Representation (Week 4)/8 - 5 - Examples and Intuitions I (7 min).srt 13.1 KB |
VIII. Neural Networks Representation (Week 4)/8 - 6 - Examples and Intuitions II (10 min).mp4 14.0 MB |
VIII. Neural Networks Representation (Week 4)/8 - 6 - Examples and Intuitions II (10 min).srt 17.1 KB |
VIII. Neural Networks Representation (Week 4)/8 - 7 - Multiclass Classification (4 min).mp4 4.8 MB |
VIII. Neural Networks Representation (Week 4)/8 - 7 - Multiclass Classification (4 min).srt 7.4 KB |
VIII. Neural Networks Representation (Week 4)/docs_slides_Lecture8.pdf 5.0 MB |
VIII. Neural Networks Representation (Week 4)/docs_slides_Lecture8.pptx 40.4 MB |
VIII. Neural Networks Representation (Week 4)/ex3.zip 7.5 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 1 - Deciding What to Try Next (6 min).mp4 6.9 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 1 - Deciding What to Try Next (6 min).srt 12.4 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 2 - Evaluating a Hypothesis (8 min).mp4 8.5 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 2 - Evaluating a Hypothesis (8 min).srt 11.5 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 3 - Model Selection and Train_Validation_Test Sets (12 min).mp4 14.1 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 3 - Model Selection and Train_Validation_Test Sets (12 min).srt 24.6 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 4 - Diagnosing Bias vs. Variance (8 min).mp4 9.0 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 4 - Diagnosing Bias vs. Variance (8 min).srt 16.1 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 5 - Regularization and Bias_Variance (11 min).mp4 12.6 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 5 - Regularization and Bias_Variance (11 min).srt 22.5 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 6 - Learning Curves (12 min).mp4 12.9 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 6 - Learning Curves (12 min).srt 24.7 KB |
X. Advice for Applying Machine Learning (Week 6)/10 - 7 - Deciding What to Do Next Revisited (7 min).mp4 8.2 MB |
X. Advice for Applying Machine Learning (Week 6)/10 - 7 - Deciding What to Do Next Revisited (7 min).srt 14.1 KB |
X. Advice for Applying Machine Learning (Week 6)/docs_slides_Lecture10.pdf 1.5 MB |
X. Advice for Applying Machine Learning (Week 6)/docs_slides_Lecture10.pptx 3.4 MB |
X. Advice for Applying Machine Learning (Week 6)/ex5.zip 177.0 KB |
XI. Machine Learning System Design (Week 6)/11 - 1 - Prioritizing What to Work On (10 min).mp4 11.2 MB |
XI. Machine Learning System Design (Week 6)/11 - 1 - Prioritizing What to Work On (10 min).srt 19.7 KB |
XI. Machine Learning System Design (Week 6)/11 - 2 - Error Analysis (13 min).mp4 15.4 MB |
XI. Machine Learning System Design (Week 6)/11 - 2 - Error Analysis (13 min).srt 27.5 KB |
XI. Machine Learning System Design (Week 6)/11 - 3 - Error Metrics for Skewed Classes (12 min).mp4 13.3 MB |
XI. Machine Learning System Design (Week 6)/11 - 3 - Error Metrics for Skewed Classes (12 min).srt 22.1 KB |
XI. Machine Learning System Design (Week 6)/11 - 4 - Trading Off Precision and Recall (14 min).mp4 16.0 MB |
XI. Machine Learning System Design (Week 6)/11 - 4 - Trading Off Precision and Recall (14 min).srt 28.6 KB |
XI. Machine Learning System Design (Week 6)/11 - 5 - Data For Machine Learning (11 min).mp4 12.9 MB |
XI. Machine Learning System Design (Week 6)/11 - 5 - Data For Machine Learning (11 min).srt 23.2 KB |
XI. Machine Learning System Design (Week 6)/docs_slides_Lecture11.pdf 497.6 KB |
XI. Machine Learning System Design (Week 6)/docs_slides_Lecture11.pptx 1.9 MB |
XII. Support Vector Machines (Week 7)/12 - 1 - Optimization Objective (15 min).mp4 16.7 MB |
XII. Support Vector Machines (Week 7)/12 - 1 - Optimization Objective (15 min).srt 29.4 KB |
XII. Support Vector Machines (Week 7)/12 - 2 - Large Margin Intuition (11 min).mp4 11.8 MB |
XII. Support Vector Machines (Week 7)/12 - 2 - Large Margin Intuition (11 min).srt 21.3 KB |
XII. Support Vector Machines (Week 7)/12 - 3 - Mathematics Behind Large Margin Classification (Optional) (20 min).mp4 21.8 MB |
XII. Support Vector Machines (Week 7)/12 - 3 - Mathematics Behind Large Margin Classification (Optional) (20 min).srt 35.9 KB |
XII. Support Vector Machines (Week 7)/12 - 4 - Kernels I (16 min).mp4 17.6 MB |
XII. Support Vector Machines (Week 7)/12 - 4 - Kernels I (16 min).srt 29.1 KB |
XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min) (1).mp4 17.4 MB |
XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min) (1).srt 30.7 KB |
XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min).mp4 17.4 MB |
XII. Support Vector Machines (Week 7)/12 - 5 - Kernels II (16 min).srt 30.7 KB |
XII. Support Vector Machines (Week 7)/12 - 6 - Using An SVM (21 min).mp4 24.0 MB |
XII. Support Vector Machines (Week 7)/12 - 6 - Using An SVM (21 min).srt 43.5 KB |
XII. Support Vector Machines (Week 7)/docs_slides_Lecture12.pdf 2.3 MB |
XII. Support Vector Machines (Week 7)/docs_slides_Lecture12.pptx 5.4 MB |
XII. Support Vector Machines (Week 7)/ex6.zip 896.4 KB |
XIII. Clustering (Week 8)/13 - 1 - Unsupervised Learning Introduction (3 min).mp4 3.8 MB |
XIII. Clustering (Week 8)/13 - 1 - Unsupervised Learning- Introduction (3 min).srt 7.0 KB |
XIII. Clustering (Week 8)/13 - 2 - K-Means Algorithm (13 min).mp4 13.8 MB |
XIII. Clustering (Week 8)/13 - 2 - K-Means Algorithm (13 min).srt 26.2 KB |
XIII. Clustering (Week 8)/13 - 3 - Optimization Objective (7 min).mp4 8.1 MB |
XIII. Clustering (Week 8)/13 - 3 - Optimization Objective (7 min).srt 13.7 KB |
XIII. Clustering (Week 8)/13 - 4 - Random Initialization (8 min).mp4 8.7 MB |
XIII. Clustering (Week 8)/13 - 4 - Random Initialization (8 min).srt 16.2 KB |
XIII. Clustering (Week 8)/13 - 5 - Choosing the Number of Clusters (8 min).mp4 9.4 MB |
XIII. Clustering (Week 8)/13 - 5 - Choosing the Number of Clusters (8 min).srt 17.9 KB |
XIII. Clustering (Week 8)/docs_slides_Lecture13.pdf 2.2 MB |
XIII. Clustering (Week 8)/docs_slides_Lecture13.pptx 2.8 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 1 - Motivation I Data Compression (10 min).mp4 14.3 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 1 - Motivation I- Data Compression (10 min).srt 20.1 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 2 - Motivation II Visualization (6 min).mp4 6.3 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 2 - Motivation II- Visualization (6 min).srt 10.2 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 3 - Principal Component Analysis Problem Formulation (9 min).mp4 10.5 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 3 - Principal Component Analysis Problem Formulation (9 min).srt 18.4 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 4 - Principal Component Analysis Algorithm (15 min).mp4 17.8 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 4 - Principal Component Analysis Algorithm (15 min).srt 28.6 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 5 - Choosing the Number of Principal Components (11 min).mp4 11.8 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 5 - Choosing the Number of Principal Components (11 min).srt 21.1 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 6 - Reconstruction from Compressed Representation (4 min).mp4 5.0 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 6 - Reconstruction from Compressed Representation (4 min).srt 7.6 KB |
XIV. Dimensionality Reduction (Week 8)/14 - 7 - Advice for Applying PCA (13 min).mp4 14.7 MB |
XIV. Dimensionality Reduction (Week 8)/14 - 7 - Advice for Applying PCA (13 min).srt 26.3 KB |
XIV. Dimensionality Reduction (Week 8)/docs_slides_Lecture14.pdf 1.6 MB |
XIV. Dimensionality Reduction (Week 8)/docs_slides_Lecture14.pptx 3.6 MB |
XIV. Dimensionality Reduction (Week 8)/ex7.zip 11.0 MB |
XIX. Conclusion/19 - 1 - Summary and Thank You (5 min).mp4 6.1 MB |
XIX. Conclusion/19 - 1 - Summary and Thank You (5 min).srt 8.1 KB |
XV. Anomaly Detection (Week 9)/15 - 1 - Problem Motivation (8 min).mp4 8.3 MB |
XV. Anomaly Detection (Week 9)/15 - 1 - Problem Motivation (8 min).srt 16.0 KB |
XV. Anomaly Detection (Week 9)/15 - 2 - Gaussian Distribution (10 min).mp4 11.7 MB |
XV. Anomaly Detection (Week 9)/15 - 2 - Gaussian Distribution (10 min).srt 20.6 KB |
XV. Anomaly Detection (Week 9)/15 - 3 - Algorithm (12 min).mp4 14.0 MB |
XV. Anomaly Detection (Week 9)/15 - 3 - Algorithm (12 min).srt 23.5 KB |
XV. Anomaly Detection (Week 9)/15 - 4 - Developing and Evaluating an Anomaly Detection System (13 min).mp4 15.2 MB |
XV. Anomaly Detection (Week 9)/15 - 4 - Developing and Evaluating an Anomaly Detection System (13 min).srt 27.3 KB |
XV. Anomaly Detection (Week 9)/15 - 5 - Anomaly Detection vs. Supervised Learning (8 min).mp4 9.3 MB |
XV. Anomaly Detection (Week 9)/15 - 5 - Anomaly Detection vs. Supervised Learning (8 min).srt 16.4 KB |
XV. Anomaly Detection (Week 9)/15 - 6 - Choosing What Features to Use (12 min).mp4 14.1 MB |
XV. Anomaly Detection (Week 9)/15 - 6 - Choosing What Features to Use (12 min).srt 25.1 KB |
XV. Anomaly Detection (Week 9)/15 - 7 - Multivariate Gaussian Distribution (Optional) (14 min).mp4 15.9 MB |
XV. Anomaly Detection (Week 9)/15 - 7 - Multivariate Gaussian Distribution (Optional) (14 min).srt 27.4 KB |
XV. Anomaly Detection (Week 9)/15 - 8 - Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min).mp4 16.3 MB |
XV. Anomaly Detection (Week 9)/15 - 8 - Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min).srt 26.3 KB |
XV. Anomaly Detection (Week 9)/docs_slides_Lecture15.pdf 3.3 MB |
XV. Anomaly Detection (Week 9)/docs_slides_Lecture15.pptx 6.0 MB |
XVI. Recommender Systems (Week 9)/16 - 1 - Problem Formulation (8 min).mp4 10.7 MB |
XVI. Recommender Systems (Week 9)/16 - 1 - Problem Formulation (8 min).srt 16.8 KB |
XVI. Recommender Systems (Week 9)/16 - 2 - Content Based Recommendations (15 min).mp4 16.9 MB |
XVI. Recommender Systems (Week 9)/16 - 2 - Content Based Recommendations (15 min).srt 28.6 KB |
XVI. Recommender Systems (Week 9)/16 - 3 - Collaborative Filtering (10 min).mp4 11.8 MB |
XVI. Recommender Systems (Week 9)/16 - 3 - Collaborative Filtering (10 min).srt 20.2 KB |
XVI. Recommender Systems (Week 9)/16 - 4 - Collaborative Filtering Algorithm (9 min).mp4 10.3 MB |
XVI. Recommender Systems (Week 9)/16 - 4 - Collaborative Filtering Algorithm (9 min).srt 16.5 KB |
XVI. Recommender Systems (Week 9)/16 - 5 - Vectorization Low Rank Matrix Factorization (8 min).mp4 9.7 MB |
XVI. Recommender Systems (Week 9)/16 - 5 - Vectorization- Low Rank Matrix Factorization (8 min).srt 16.3 KB |
XVI. Recommender Systems (Week 9)/16 - 6 - Implementational Detail Mean Normalization (9 min).mp4 9.7 MB |
XVI. Recommender Systems (Week 9)/16 - 6 - Implementational Detail- Mean Normalization (9 min).srt 16.6 KB |
XVI. Recommender Systems (Week 9)/docs_slides_Lecture16.pdf 1.4 MB |
XVI. Recommender Systems (Week 9)/docs_slides_Lecture16.pptx 3.6 MB |
XVI. Recommender Systems (Week 9)/ex8.zip 794.8 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 1 - Learning With Large Datasets (6 min).mp4 6.5 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 1 - Learning With Large Datasets (6 min).srt 7.9 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 2 - Stochastic Gradient Descent (13 min).mp4 15.3 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 2 - Stochastic Gradient Descent (13 min).srt 18.1 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 3 - Mini-Batch Gradient Descent (6 min).mp4 7.3 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 3 - Mini-Batch Gradient Descent (6 min).srt 7.8 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 4 - Stochastic Gradient Descent Convergence (12 min).mp4 13.3 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 4 - Stochastic Gradient Descent Convergence (12 min).srt 16.2 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 5 - Online Learning (13 min).mp4 14.9 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 5 - Online Learning (13 min).srt 27.7 KB |
XVII. Large Scale Machine Learning (Week 10)/17 - 6 - Map Reduce and Data Parallelism (14 min).mp4 16.1 MB |
XVII. Large Scale Machine Learning (Week 10)/17 - 6 - Map Reduce and Data Parallelism (14 min).srt 28.9 KB |
XVII. Large Scale Machine Learning (Week 10)/docs_slides_Lecture17.pdf 2.0 MB |
XVII. Large Scale Machine Learning (Week 10)/docs_slides_Lecture17.pptx 3.8 MB |
XVIII. Application Example Photo OCR/18 - 1 - Problem Description and Pipeline (7 min).mp4 7.9 MB |
XVIII. Application Example Photo OCR/18 - 1 - Problem Description and Pipeline (7 min).srt 14.7 KB |
XVIII. Application Example Photo OCR/18 - 2 - Sliding Windows (15 min).mp4 16.5 MB |
XVIII. Application Example Photo OCR/18 - 2 - Sliding Windows (15 min).srt 31.5 KB |
XVIII. Application Example Photo OCR/18 - 3 - Getting Lots of Data and Artificial Data (16 min).mp4 18.8 MB |
XVIII. Application Example Photo OCR/18 - 3 - Getting Lots of Data and Artificial Data (16 min).srt 35.2 KB |
XVIII. Application Example Photo OCR/18 - 4 - Ceiling Analysis What Part of the Pipeline to Work on Next (14 min).mp4 16.1 MB |
XVIII. Application Example Photo OCR/18 - 4 - Ceiling Analysis- What Part of the Pipeline to Work on Next (14 min).srt 30.5 KB |
XVIII. Application Example Photo OCR/docs_slides_Lecture18.pdf 2.0 MB |
XVIII. Application Example Photo OCR/docs_slides_Lecture18.pptx 6.1 MB |
- Torrent indexed: 10 years
- Torrent updated: Friday 1st of May 2015 03:30:01 PM
- Torrent hash: E9D6C0D130949E16F3F8D7105241D28B55590A18
- Torrent size: 1.5 GB
- Torrent category: other

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