Stanford University offers a Machine Learning Course.
The course is 11 weeks long, tuition is free (or $49 if you want a certificate upon completion of the course).
The next session begins March 21, enrollment ends March 12.
Here's the syllabus and enrollment link:
https://www.coursera.org/learn/machine-learning/
See also:
https://www.coursera.org/about/partners
http://www.blueowlpress.com/machine-learning-course-from-stanford-and-coursera
"The ever-popular machine learning course sponsored by Coursera and Stanford University, taught by Andrew Ng, is beginning a new session.
Over 10,000 people have already enrolled in this session."
The course is 11 weeks long, tuition is free (or $49 if you want a certificate upon completion of the course).
The next session begins March 21, enrollment ends March 12.
Here's the syllabus and enrollment link:
https://www.coursera.org/learn/machine-learning/
Code:
Syllabus
Week 1
Introduction
Linear Regression with One Variable
Linear Algebra Review
Welcome
Introduction
Review
Other Materials
Model and Cost Function
Parameter Learning
Review
Linear Algebra Review
Review
Quiz: Introduction
Quiz: Linear Regression with One Variable
Week 2
Linear Regression with Multiple Variables
Octave Tutorial
Environment Setup Instructions
Multivariate Linear Regression
Computing Parameters Analytically
Review
Octave Tutorial
Submitting Programming Assignments
Review
Quiz: Linear Regression with Multiple Variables
Assignment: Linear Regression
Quiz: Octave Tutorial
Week 3
Logistic Regression
Regularization
Classification and Representation
Logistic Regression Model
Multiclass Classification
Review
Solving the Problem of Overfitting
Review
Quiz: Logistic Regression
Assignment: Logistic Regression
Quiz: Regularization
Week 4
Neural Networks: Representation
Motivations
Neural Networks
Applications
Review
Quiz: Neural Networks: Representation
Assignment: Multi-class Classification and Neural Networks
Week 5
Neural Networks: Learning
Cost Function and Backpropagation
Backpropagation in Practice
Application of Neural Networks
Review
Quiz: Neural Networks: Learning
Assignment: Neural Network Learning
Week 6
Advice for Applying Machine Learning
Machine Learning System Design
Evaluating a Learning Algorithm
Bias vs. Variance
Review
Building a Spam Classifier
Handling Skewed Data
Using Large Data Sets
Review
Quiz: Advice for Applying Machine Learning
Assignment: Regularized Linear Regression and Bias/Variance
Quiz: Machine Learning System Design
Week 7
Support Vector Machines
Large Margin Classification
Kernels
SVMs in Practice
Review
Quiz: Support Vector Machines
Assignment: Support Vector Machines
Week 8
Unsupervised Learning
Dimensionality Reduction
Clustering
Review
Motivation
Principal Component Analysis
Applying PCA
Review
Quiz: Unsupervised Learning
Quiz: Principal Component Analysis
Assignment: K-Means Clustering and PCA
Week 9
Anomaly Detection
Recommender Systems
Density Estimation
Building an Anomaly Detection System
Multivariate Gaussian Distribution (Optional)
Review
Predicting Movie Ratings
Collaborative Filtering
Low Rank Matrix Factorization
Review
Quiz: Anomaly Detection
Quiz: Recommender Systems
Assignment: Anomaly Detection and Recommender Systems
Week 10
Large Scale Machine Learning
Gradient Descent with Large Datasets
Advanced Topics
Review
Quiz: Large Scale Machine Learning
Week 11
Application Example: Photo OCR
Photo OCR
Review
Conclusion
Quiz: Application: Photo OCRSee also:
https://www.coursera.org/about/partners
http://www.blueowlpress.com/machine-learning-course-from-stanford-and-coursera
"The ever-popular machine learning course sponsored by Coursera and Stanford University, taught by Andrew Ng, is beginning a new session.
Over 10,000 people have already enrolled in this session."
