Coursera machine learning course resources.

Bayesian Reasoning and Machine Learning http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf

https://class.coursera.org/ml/lecture/preview

• Introduction
• Linear regression with one variable
• Linear Algebra review (Optional)

• Linear regression with multiple variables
• Octave tutorial
• Programming Exercise 1: Linear Regression

• Logistic regression
• Regularization
• Programming Exercise 2: Logistic Regression

• Neural Networks: Representation
• Programming Exercise 3: Multi-class Classification and Neural Networks

• Neural Networks: Learning
• Programming Exercise 4: Neural Networks Learning

• Advice for applying machine learning
• Machine learning system design
• Programming Exercise 5: Regularized Linear Regression and Bias v.s. Variance

• Support vector machines
• Programming Exercise 6: Support Vector Machines

• Clustering
• Dimensionality reduction
• Programming Exercise 7: K-means Clustering and Principal Component Analysis

• Anomaly Detection
• Recommender Systems
• Programming Exercise 8: Anomaly Detection and Recommender Systems

• Large scale machine learning
• Application example: Photo OCR