# Accomplishment of the Stanford Machine Learning Course on Coursera

You don't know about **coursera.org/**? Briefly, it proposes **online courses** from different universities (american but not only).

I studied the **Machine Learning Course of Andrew Ng from Stanford university** (*starting on April 23, 2012*):

The course duration is

*10 weeks*. The course is made of

*lectures*(video),

*Review Questions*(Quizz), and

*Programming Exercices*(in Octave).

The amont of work is about

*5 to 7 hours per week*.

*Review Questions*and

*Programming Exercices*have to be submit each week with deadlines.

The overview of the Machine Learning Course content is the following:

**Week 1**

- Introduction

- Linear Regression with One Variable

- Review Questions (for the week's topics)

- (Optional) Linear Algebra Review

**Week 2**

- Linear Regression with Multiple Variables

- Octave Tutorial

- Review Questions (for the week's topics)

- Programming Exercise 1 : Linear regression

**Week 3**

- Logistic Regression

- Regularization

- Review Questions (for the week's topics)

- Programming Exercise 2 : Logistic regression

**Week 4**

- Neural Networks: Representation

- Review Questions (for the week's topics)

- Programming Exercise 3 : Multi-class classification and neural networks

**Week 5**

- Neural Networks: Learning

- Review Questions (for the week's topics)

- Programming Exercise (Neural network learning)

**Week 6**

- Advice for Applying Machine Learning

- Machine Learning System Design

- Review Questions (for the week's topics)

- Programming Exercise : Bias-variance

**Week 7**

- Support Vector Machines (SVMs)

- Review Questions (for the week's topics)

- Programming Exercise : SVMs

**Week 8**

- Clustering

- Dimensionality Reduction

- Review Questions (for the week's topics)

- Programming Exercise : K-Means and PCA

**Week 9**

- Anomaly Detection

- Recommender Systems

- Review Questions (for the week's topics)

- Programming Exercise : Anomaly Detection and Recommender Systems

**Week 10**

- Large-Scale Machine Learning

- Example of an application of machine learning

- Review Questions (for the week's topics)