This course (CS229) — taught by Professor Andrew Ng — provides a broad introduction to machine learning and statistical pattern recognition.
Topics include supervised learning, unsupervised learning, learning theory, reinforcement learning and adaptive control.
Recent applications of machine learning, such as to robotic control, data mining, autonomous navigation, bioinformatics, speech recognition, and text and web data processing are also discussed.
Instructor: Andrew Ng.
Price: Free
Similar Posts You May Like:
Become a Data Scientist with Python 
Hands-On Python and R In Data Science 
Learning From Data: An Introductory Machine Learning Course – Free 
Learn About Data Manipulation in R Programming – Free Course 
Learn How To Put Your Machine Learning Models Into Production 
Introduction to Databases (Stanford) 
Introduction to Algorithms (MIT) 
MapReduce and Hadoop Tutorial 
Learn About R Programming for Data Statistical Computing – Free Course 
Python Programming: Complex Decisions and Events – Free Course
RSS - Posts