#andrewng#cs229#supervisedlearning
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Beginner. No background in the topic needed.
2.6M views18 years ago11 recommendations
AI and machine learningComputer scienceNeural networks and deep learningClassic machine learningAlgorithms
Andrew Ng provides an introductory overview of machine learning, covering supervised learning, unsupervised learning, learning theory, and reinforcement learning.
Lecture by Professor Andrew Ng for Machine Learning (CS 229) in the Stanford Computer Science department. Professor Ng provides an overview of the course in this introductory meeting. This course 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. Complete Playlist for the Course: youtube.com/view_play_list?p=A89DCFA6ADACE599 CS 229 Course Website: stanford.edu/class/cs229/ Stanford University: stanford.edu/ Stanford University Channel on YouTube: youtube.com/stanfordWhat people say. Widely recommended as the gold standard introduction to the mathematical foundations of machine learning.
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