PushBT Magnet/Torrent

Categories

Recommend Tools

  • Convert torrent to magnet
  • Convert torrent to magnet

fileCoursera-chine-Learning--xZQI

Coursera chine Learning Andrew Ng
  • MP401. Introduction (Week 1)\\/1 - 1 - Welcome (7 min).mp411.95MB
  • MP401. Introduction (Week 1)\\/1 - 2 - What is chine Learning- (7 min).mp49.35MB
  • MP401. Introduction (Week 1)\\/1 - 3 - Supervised Learning (12 min).mp413.45MB
  • MP401. Introduction (Week 1)\\/1 - 4 - Unsupervised Learning (14 min).mp416.66MB
  • PDF01. Introduction (Week 1)\\/docs-slides-Lecture1.pdf3.30MB
  • PPTX01. Introduction (Week 1)\\/docs-slides-Lecture1.pptx4.02MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 1 - Model Representation (8 min).mp49.00MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 2 - Cost Function (8 min).mp49.05MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 3 - Cost Function - Intuition I (11 min).mp412.24MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 4 - Cost Function - Intuition II (9 min).mp411.36MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 5 - Gradient Descent (11 min).mp413.50MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 6 - Gradient Descent Intuition (12 min).mp413.03MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 7 - Gradient Descent For Linear Regression (10 min).mp412.18MB
  • MP402. Linear Regression with One Variable (Week 1)\\/2 - 8 - What-\s Next (6 min).mp46.08MB
  • PDF02. Linear Regression with One Variable (Week 1)\\/docs-slides-Lecture2.pdf2.88MB
  • PPTX02. Linear Regression with One Variable (Week 1)\\/docs-slides-Lecture2.pptx5.35MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 1 - trices and Vectors (9 min).mp49.56MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 2 - Addition and Scalar Multiplication (7 min).mp47.46MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 3 - trix Vector Multiplication (14 min).mp415.00MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 4 - trix Matrix Multiplication (11 min).mp412.59MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 5 - trix Multiplication Properties (9 min).mp49.81MB
  • MP403. Linear Algebra Review (Week 1 Optional)\\/3 - 6 - Inverse and Transpose (11 min).mp412.87MB
  • PDF03. Linear Algebra Review (Week 1 Optional)\\/docs-slides-Lecture3.pdf1.80MB
  • PPTX03. Linear Algebra Review (Week 1 Optional)\\/docs-slides-Lecture3.pptx4.92MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 1 - Multiple Features (8 min).mp48.84MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 2 - Gradient Descent for Multiple Variables (5 min).mp45.78MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 3 - Gradient Descent in Practice I - Feature Scaling (9 min).mp49.46MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 4 - Gradient Descent in Practice II - Learning Rate (9 min).mp49.26MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 5 - Features and Polynomial Regression (8 min).mp48.26MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 6 - Norl Equation (16 min).mp417.13MB
  • MP404. Linear Regression with Multiple Variables (Week 2)\\/4 - 7 - Norl Equation Noninvertibility (Optional) (6 min).mp46.24MB
  • PDF04. Linear Regression with Multiple Variables (Week 2)\\/docs-slides-Lecture4.pdf1.70MB
  • PPTX04. Linear Regression with Multiple Variables (Week 2)\\/docs-slides-Lecture4.pptx4.40MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 1 - Basic Operations (14 min).mp417.72MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 2 - Moving Data Around (16 min).mp420.77MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 3 - Computing on Data (13 min).mp415.25MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 4 - Plotting Data (10 min).mp413.32MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 5 - Control Statements- for while if statements (13 min).mp416.49MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 6 - Vectorization (14 min).mp416.09MB
  • MP405. Octe Tutorial (Week 2)\\/5 - 7 - Working on and Submitting Programming Exercises (4 min).mp45.46MB
  • PDF05. Octe Tutorial (Week 2)\\/docs-slides-Lecture5.pdf242.37KB
  • PPTX05. Octe Tutorial (Week 2)\\/docs-slides-Lecture5.pptx407.28KB
  • MP406. Logistic Regression (Week 3)\\/6 - 1 - Classification (8 min).mp48.77MB
  • MP406. Logistic Regression (Week 3)\\/6 - 2 - Hypothesis Representation (7 min).mp48.34MB
  • MP406. Logistic Regression (Week 3)\\/6 - 3 - Decision Boundary (15 min).mp416.74MB
  • MP406. Logistic Regression (Week 3)\\/6 - 4 - Cost Function (11 min).mp413.09MB
  • MP406. Logistic Regression (Week 3)\\/6 - 5 - Simplified Cost Function and Gradient Descent (10 min).mp411.96MB
  • MP406. Logistic Regression (Week 3)\\/6 - 6 - Advanced Optimization (14 min).mp418.15MB
  • MP406. Logistic Regression (Week 3)\\/6 - 7 - Multiclass Classification- One-vs-all (6 min).mp46.93MB
  • PDF06. Logistic Regression (Week 3)\\/docs-slides-Lecture6.pdf2.12MB
  • PPTX06. Logistic Regression (Week 3)\\/docs-slides-Lecture6.pptx3.82MB
  • MP407. Regularization (Week 3)\\/7 - 1 - The Problem of Overfitting (10 min).mp411.15MB
  • MP407. Regularization (Week 3)\\/7 - 2 - Cost Function (10 min).mp411.63MB
  • MP407. Regularization (Week 3)\\/7 - 3 - Regularized Linear Regression (11 min).mp412.00MB
  • MP407. Regularization (Week 3)\\/7 - 4 - Regularized Logistic Regression (9 min).mp410.89MB
  • PDF07. Regularization (Week 3)\\/docs-slides-Lecture7.pdf2.34MB
  • PPTX07. Regularization (Week 3)\\/docs-slides-Lecture7.pptx2.59MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 1 - Non-linear Hypotheses (10 min).mp410.88MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 2 - Neurons and the Brain (8 min).mp49.89MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 3 - Model Representation I (12 min).mp413.51MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 4 - Model Representation II (12 min).mp413.45MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 5 - Examples and Intuitions I (7 min).mp47.89MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 6 - Examples and Intuitions II (10 min).mp414.00MB
  • MP408. Neural Networks Representation (Week 4)\\/8 - 7 - Multiclass Classification (4 min).mp44.83MB
  • PDF08. Neural Networks Representation (Week 4)\\/docs-slides-Lecture8.pdf4.97MB
  • PPTX08. Neural Networks Representation (Week 4)\\/docs-slides-Lecture8.pptx40.36MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 1 - Cost Function (7 min).mp47.66MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 2 - Backpropagation Algorithm (12 min).mp413.94MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 3 - Backpropagation Intuition (13 min).mp415.44MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 4 - Implementation Note- Unrolling Parameters (8 min).mp49.38MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 5 - Gradient Checking (12 min).mp413.50MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 6 - Random Initialization (7 min).mp47.56MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 7 - Putting It Together (14 min).mp416.30MB
  • MP409. Neural Networks Learning (Week 5)\\/9 - 8 - Autonomous Driving (7 min).mp414.88MB
  • PDF09. Neural Networks Learning (Week 5)\\/docs-slides-Lecture9.pdf3.37MB
  • PPTX09. Neural Networks Learning (Week 5)\\/docs-slides-Lecture9.pptx4.96MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 1 - Deciding What to Try Next (6 min).mp46.86MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 2 - Evaluating a Hypothesis (8 min).mp48.48MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 3 - Model Selection and Train-Validation-Test Sets (12 min).mp414.07MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 4 - Diagnosing Bias vs. Variance (8 min).mp48.97MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 5 - Regularization and Bias-Variance (11 min).mp412.60MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 6 - Learning Curves (12 min).mp412.92MB
  • MP410. Advice for Applying chine Learning (Week 6)\\/10 - 7 - Deciding What to Do Next Revisited (7 min).mp48.18MB
  • PDF10. Advice for Applying chine Learning (Week 6)\\/docs-slides-Lecture10.pdf1.48MB
  • PPTX10. Advice for Applying chine Learning (Week 6)\\/docs-slides-Lecture10.pptx3.35MB
  • MP411. chine Learning System Design (Week 6)\\/11 - 1 - Prioritizing What to Work On (10 min).mp411.17MB
  • MP411. chine Learning System Design (Week 6)\\/11 - 2 - Error Analysis (13 min).mp415.43MB
  • MP411. chine Learning System Design (Week 6)\\/11 - 3 - Error Metrics for Skewed Classes (12 min).mp413.25MB
  • MP411. chine Learning System Design (Week 6)\\/11 - 4 - Trading Off Precision and Recall (14 min).mp415.99MB
  • MP411. chine Learning System Design (Week 6)\\/11 - 5 - Data For Machine Learning (11 min).mp412.87MB
  • PDF11. chine Learning System Design (Week 6)\\/docs-slides-Lecture11.pdf497.64KB
  • PPTX11. chine Learning System Design (Week 6)\\/docs-slides-Lecture11.pptx1.93MB
  • MP412. Support Vector chines (Week 7)\\/12 - 1 - Optimization ob<x>jective (15 min).mp416.65MB
  • MP412. Support Vector chines (Week 7)\\/12 - 2 - Large Margin Intuition (11 min).mp411.81MB
  • MP412. Support Vector chines (Week 7)\\/12 - 3 - Mathematics Behind Large Margin Classification (Optional) (20 min).mp421.83MB
  • MP412. Support Vector chines (Week 7)\\/12 - 4 - Kernels I (16 min).mp417.57MB
  • MP412. Support Vector chines (Week 7)\\/12 - 5 - Kernels II (16 min).mp417.45MB
  • MP412. Support Vector chines (Week 7)\\/12 - 6 - Using An SVM (21 min).mp423.95MB
  • PDF12. Support Vector chines (Week 7)\\/docs-slides-Lecture12.pdf2.30MB
  • PPTX12. Support Vector chines (Week 7)\\/docs-slides-Lecture12.pptx5.39MB
  • MP413. Clustering (Week 8)\\/13 - 1 - Unsupervised Learning- Introduction (3 min).mp43.80MB
  • MP413. Clustering (Week 8)\\/13 - 2 - K-Means Algorithm (13 min).mp413.81MB
  • MP413. Clustering (Week 8)\\/13 - 3 - Optimization ob<x>jective (7 min).mp48.15MB
  • MP413. Clustering (Week 8)\\/13 - 4 - Random Initialization (8 min).mp48.67MB
  • MP413. Clustering (Week 8)\\/13 - 5 - Choosing the Number of Clusters (8 min).mp49.40MB
  • PDF13. Clustering (Week 8)\\/docs-slides-Lecture13.pdf2.17MB
  • PPTX13. Clustering (Week 8)\\/docs-slides-Lecture13.pptx2.79MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 1 - Motivation I- Data Compression (10 min).mp414.31MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 2 - Motivation II- Visualization (6 min).mp46.30MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 3 - Principal Component Analysis Problem Formulation (9 min).mp410.45MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 4 - Principal Component Analysis Algorithm (15 min).mp417.79MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 5 - Choosing the Number of Principal Components (11 min).mp411.84MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 6 - Reconstruction from Compressed Representation (4 min).mp44.98MB
  • MP414. Dimensionality Reduction (Week 8)\\/14 - 7 - Advice for Applying PCA (13 min).mp414.70MB
  • PDF14. Dimensionality Reduction (Week 8)\\/docs-slides-Lecture14.pdf1.61MB
  • PPTX14. Dimensionality Reduction (Week 8)\\/docs-slides-Lecture14.pptx3.62MB
  • MP415. Anoly Detection (Week 9)\\/15 - 1 - Problem Motivation (8 min).mp48.35MB
  • MP415. Anoly Detection (Week 9)\\/15 - 2 - Gaussian Distribution (10 min).mp411.69MB
  • MP415. Anoly Detection (Week 9)\\/15 - 3 - Algorithm (12 min).mp413.95MB
  • MP415. Anoly Detection (Week 9)\\/15 - 4 - Developing and Evaluating an Anomaly Detection System (13 min).mp415.15MB
  • MP415. Anoly Detection (Week 9)\\/15 - 5 - Anomaly Detection vs. Supervised Learning (8 min).mp49.28MB
  • MP415. Anoly Detection (Week 9)\\/15 - 6 - Choosing What Features to Use (12 min).mp414.12MB
  • MP415. Anoly Detection (Week 9)\\/15 - 7 - Multivariate Gaussian Distribution (Optional) (14 min).mp415.93MB
  • MP415. Anoly Detection (Week 9)\\/15 - 8 - Anomaly Detection using the Multivariate Gaussian Distribution (Optional) (14 min).mp416.34MB
  • PDF15. Anoly Detection (Week 9)\\/docs-slides-Lecture15.pdf3.33MB
  • PPTX15. Anoly Detection (Week 9)\\/docs-slides-Lecture15.pptx6.05MB
  • MP416. Recommender Systems (Week 9)\\/16 - 1 - Problem Formulation (8 min).mp410.67MB
  • MP416. Recommender Systems (Week 9)\\/16 - 2 - Content ba<x>sed Recommendations (15 min).mp416.93MB
  • MP416. Recommender Systems (Week 9)\\/16 - 3 - Collaborative Filtering (10 min).mp411.75MB
  • MP416. Recommender Systems (Week 9)\\/16 - 4 - Collaborative Filtering Algorithm (9 min).mp410.31MB
  • MP416. Recommender Systems (Week 9)\\/16 - 5 - Vectorization- Low Rank trix Factorization (8 min).mp49.68MB
  • MP416. Recommender Systems (Week 9)\\/16 - 6 - Implementational Detail- Mean Norlization (9 min).mp49.71MB
  • PDF16. Recommender Systems (Week 9)\\/docs-slides-Lecture16.pdf1.42MB
  • PPTX16. Recommender Systems (Week 9)\\/docs-slides-Lecture16.pptx3.60MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 1 - Learning With Large Datasets (6 min).mp46.50MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 2 - Stochastic Gradient Descent (13 min).mp415.33MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 3 - Mini-Batch Gradient Descent (6 min).mp47.32MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 4 - Stochastic Gradient Descent Convergence (12 min).mp413.33MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 5 - Online Learning (13 min).mp414.91MB
  • MP417. Large Scale chine Learning (Week 10)\\/17 - 6 - Map Reduce and Data Paralleli (14 min).mp416.06MB
  • PDF17. Large Scale chine Learning (Week 10)\\/docs-slides-Lecture17.pdf1.98MB
  • PPTX17. Large Scale chine Learning (Week 10)\\/docs-slides-Lecture17.pptx3.78MB
  • MP418. Application Example Photo OCR\\/18 - 1 - Problem Desc<x>ription and Pipeline (7 min).mp47.91MB
  • MP418. Application Example Photo OCR\\/18 - 2 - Sliding Windows (15 min).mp416.52MB
  • MP418. Application Example Photo OCR\\/18 - 3 - Getting Lots of Data and Artificial Data (16 min).mp418.82MB
  • MP418. Application Example Photo OCR\\/18 - 4 - Ceiling Analysis- What Part of the Pipeline to Work on Next (14 min).mp416.11MB
  • PDF18. Application Example Photo OCR\\/docs-slides-Lecture18.pdf1.97MB
  • PPTX18. Application Example Photo OCR\\/docs-slides-Lecture18.pptx6.13MB
  • MP419. Conclusion\\/19 - 1 - Sumry and Thank You (5 min).mp46.09MB
  • PDF_ Coursera.pdf211.90KB
  • PDFHomeworks\\/02. Linear regression with one variable.pdf604.92KB
  • PDFHomeworks\\/03. Linear Algebra.pdf642.50KB
  • PDFHomeworks\\/04. Linear Regression with Multiple Variables.pdf565.50KB
  • PDFHomeworks\\/05. Octe Tutorial.pdf645.34KB
  • PDFHomeworks\\/06. Logistic Regression.pdf675.85KB
  • PDFHomeworks\\/07. Regularization.pdf609.53KB
  • PDFHomeworks\\/08. Neural Networks Representation.pdf1.07MB
  • PDFHomeworks\\/09. Neural Networks Learning.pdf605.13KB
  • PDFHomeworks\\/10. Advice for Applying chine Learning.pdf288.58KB
  • PDFHomeworks\\/11. chine Learning System Design.pdf569.57KB
  • PDFHomeworks\\/12. Support Vector chines.pdf1.92MB
  • PDFHomeworks\\/13. Clustering.pdf577.76KB
  • PDFHomeworks\\/14. Anoly Detection.pdf631.56KB
  • PDFHomeworks\\/15. Principal Component Analysis.pdf1.01MB
  • PDFHomeworks\\/16. Recommender Systems.pdf688.23KB
  • PDFHomeworks\\/17. Large Scale chine Learning.pdf611.46KB
  • PDFHomeworks\\/18. Application Photo OCR.pdf683.77KB
  • PDFHomeworks\\/View Review Questions _ Coursera.pdf147.36KB
  • PDFProgramming Assignments\\/List Assignments _ Coursera.pdf192.72KB
  • ZIPProgramming Assignments\\/mlclass-ex1-004.zip464.27KB
  • ZIPProgramming Assignments\\/mlclass-ex2-004.zip238.22KB
  • ZIPProgramming Assignments\\/mlclass-ex3-004.zip7.54MB
  • ZIPProgramming Assignments\\/mlclass-ex4-004.zip7.59MB
  • ZIPProgramming Assignments\\/mlclass-ex5-004.zip172.53KB
  • ZIPProgramming Assignments\\/mlclass-ex6-004.zip893.03KB
  • ZIPProgramming Assignments\\/mlclass-ex7-004.zip11.05MB
  • ZIPProgramming Assignments\\/mlclass-ex8-004.zip790.99KB
  • PDFWiki - Course FAQ _ Coursera.pdf98.01KB
  • PDFWiki - Octe __ tlab Tutorial _ Coursera.pdf886.17KB
  • PDFWiki - Tutoring _ Coursera.pdf2.28MB
Latest Search: 1.TDMJ-117   2.ATAD-096   3.MIBD-577   4.YSN-281   5.NSPS-121   6.PBD-204   7.PBD-001   8.SOE-945   9.DVH-331   10.ONSD-456   11.SVOMN-046   12.NFDM-273   13.MIAD-582   14.RD-009   15.NHDTA-445   16.JMD-106   17.VEQ-049   18.RBNR-053   19.DVH-276   20.JUSD-261   21.YUYG-003   22.GIGL-011   23.MXD-026   24.MIGD-592   25.MDSH-016   26.GIGL-123   27.IDBD-621   28.R18-308   29.LON-008   30.MGDN-055   31.HND-346   32.MDJY-008   33.CMI-087   34.GVG-472   35.SPRD-954   36.BDSR-344   37.CESD-741   38.OVG-098   39.PHD-002   40.SQTE-260   41.BCPV-126   42.004   43.215   44.229   45.204   46.0   47.269   48.004   49.071   50.115   51.177   52.117   53.406   54.574   55.1   56.080   57.679   58.130   59.2608   60.505   61.049   62.185   63.33   64.201   65.0   66.015   67.286   68.209   69.015   70.486   71.443   72.680   73.458   74.377   75.04   76.285   77.179   78.552   79.005   80.130   81.109   82.184   83.732   84.27   85.352   86.182   87.044   88.355   89.011   90.001   91.767   92.125   93.234   94.016   95.262   96.205   97.216   98.8   99.009   100.657   101.001   102.286   103.046   104.146   105.131   106.669   107.036   108.037   109.093   110.629   111.003