Machine Learning Andrew Ng, Stanford University [FULL COURSE]

Created by: Andrew Ng

Produced in 2016

icon
Course Description

In this class, you will learn about the most effective machine learning techniques, and gain practice implementing them and getting them to work for yourself. More importantly, you'll learn about not only the theoretical underpinnings of learning, but also gain the practical know-how needed to quickly and powerfully apply these techniques to new problems. Finally, you'll learn about some of Silicon Valley's best practices in innovation as it pertains to machine learning and AI. This course provides a broad introduction to machine learning, datamining, and statistical pattern recognition. Topics include: (i) Supervised learning (parametric/non-parametric algorithms, support vector machines, kernels, neural networks). (ii) Unsupervised learning (clustering, dimensionality reduction, recommender systems, deep learning). (iii) Best practices in machine learning (bias/variance theory; innovation process in machine learning and AI).

icon
Instructor Details

Andrew Ng

Andrew Yan-Tak Ng is a Chinese-American computer scientist, global leader in AI, inventor, business executive, investor and entrepreneur of the Silicon Valley who has made major contributions to artificial intelligence, deep learning, robotics, and machine learning.

Read More

icon
Reviews

0.0

0 total reviews

5 star 4 star 3 star 2 star 1 star
% Complete
% Complete
% Complete
% Complete
% Complete
% % % % %