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:
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9 years ago 00:34:52 525
Lecture 1. Dawn of Freedom
11 months ago 01:35:47 35
Cosmology Lecture 1
9 years ago 01:58:15 42
Special Relativity | Lecture 1
10 months ago 01:25:38 21
HIST 3394 LECTURE 1
8 years ago 01:46:33 151
Lecture 1 | The Theoretical Minimum
9 years ago 01:51:38 60
Steve Huston Lecture 1
11 years ago 02:06:29 30
Darwin’s Legacy | Lecture 1
9 years ago 01:19:50 37
Lecture 1: Overview
7 years ago 01:54:35 7
constitutional law lecture 1
8 years ago 01:46:07 147
Geography of United States Elections | Lecture 1
10 years ago 01:51:11 209
Lecture 1 | Modern Physics: Quantum Mechanics (Stanford)
10 years ago 02:40:13 30
Autodesk Maya Lecture #1 • Курс
8 years ago 01:24:49 2
Komarov, Lecture # 1
11 years ago 01:29:11 89
Classical Mechanics | Lecture 1
8 years ago 00:22:26 123
Classification of Bacteria (Antibiotics - Lecture 1)
10 years ago 01:58:46 300
Linear Algebra: Lecture 1 (Princeton University)
8 years ago 01:40:06 166
Advanced Quantum Mechanics Lecture 1
12 years ago 00:36:18 14
MIT Biology lecture 1 (Ru subs)
3 years ago 00:13:24 284
Group Theory, lecture 1.1: Symmetries
11 years ago 00:55:49 69
Abarita’s lecture, part 1
5 years ago 01:43:03 1
Cosmology | Lecture 1
4 years ago 00:48:54 1
MCENVD lecture 1
9 years ago 01:49:24 312
Lecture 1 | Modern Physics: Special Relativity (Stanford)