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Thursday, July 19, 2012

example of a complete coursera course - while many courses need to be signed up for live some are also on permanent preview - isn't the style cool?- video instruction with occasional questions pausing video until you answer

Machine Learning

Andrew Ng, Associate Professor

Learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself.

Video Lectures

I. Introduction (Week 1)

II. Linear Regression with One Variable (Week 1)

III. Linear Algebra Review (Week 1, Optional)

IV. Linear Regression with Multiple Variables (Week 2)

V. Octave Tutorial (Week 2)

VI. Logistic Regression (Week 3)

VII. Regularization (Week 3)

VIII. Neural Networks: Representation (Week 4)

IX. Neural Networks: Learning (Week 5)

X. Advice for Applying Machine Learning (Week 6)

XI. Machine Learning System Design (Week 6)

XII. Support Vector Machines (Week 7)

XIII. Clustering (Week 8)

XIV. Dimensionality Reduction (Week 8)

XV. Anomaly Detection (Week 9)

XVI. Recommender Systems (Week 9)

XVII. Large Scale Machine Learning (Week 10)

XVIII. Application Example: Photo OCR

XIX. Conclusion

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