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https://github.com/1ambda/machine-learning


https://github.com/1ambda/machine-learning

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# machine learning note

**Machine Learning** by *Andrew Ng*, Coursera

[Chapter 1](http://1ambda.github.io/machine-learning-week-1/) - Linear Regression
[Chapter 2](http://1ambda.github.io/machine-learning-week-2/) - Gradient Descent
[Chapter 3](http://1ambda.github.io/machine-learning-week-3/) - Logistic Regression
[Chapter 4](http://1ambda.github.io/machine-learning-week-4/) - Neural Network
[Chapter 5](http://1ambda.github.io/machine-learning-week-5/) - Back Propagation
[Chapter 6](http://1ambda.github.io/machine-learning-week-6/) - Practical Advices
[Chapter 7](http://1ambda.github.io/machine-learning-week-7/) - Support Vector Machine
[Chapter 8](http://1ambda.github.io/machine-learning-week-8/) - K-means, PCA Details
[Chapter 9](http://1ambda.github.io/machine-learning-week-9/) - Anomaly Detection, Recommender System
[Chapter 10](http://1ambda.github.io/machine-learning-week-10/) - Stochastic Gradient, Synthetic Data, Ceiling Analysis

**Process Mining** by *Wil Van der Alast*, Coursera

[Week 1](http://1ambda.github.io/process-mining-week1/) - Process Mining Intro
[Week 2](http://1ambda.github.io/process-mining-week2/) - Alpha Algorithm
[Week 3](http://1ambda.github.io/process-mining-week3/) - Metric, C-nets
[Week 4](http://1ambda.github.io/process-mining-week4/) - Conformance Checking, Dotted Chart
[Week 5](http://1ambda.github.io/process-mining-week5/) - Decision, Social, Organization Mining