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:
Learning From Data: An Introductory Machine Learning Course – Free 
Learn How To Put Your Machine Learning Models Into Production 
Become a Data Scientist with Python 
Introduction to Databases (Stanford) 
Master Data Science with These Four Free Courses 
Python Programming: Complex Decisions and Events – Free Course 
Learn About R Programming for Data Statistical Computing – Free Course 
MapReduce and Hadoop Tutorial 
Introduction to Algorithms (MIT) 
Data Science: Deep Learning in Python