Chevron Left
Back to Machine Learning

Machine Learning, Stanford University

4.9
97,443 ratings
24,478 reviews

About this Course

Machine learning is the science of getting computers to act without being explicitly programmed. In the past decade, machine learning has given us self-driving cars, practical speech recognition, effective web search, and a vastly improved understanding of the human genome. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. 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). The course will also draw from numerous case studies and applications, so that you'll also learn how to apply learning algorithms to building smart robots (perception, control), text understanding (web search, anti-spam), computer vision, medical informatics, audio, database mining, and other areas....

Top reviews

By QP

Jun 25, 2018

This course is extremely helpful and understandable for engineers and researchers in the CS field. Many thanks to the prof. Ng Yew Kwang for his great course as well as supporters in the course forum.

By HS

Mar 03, 2018

My first and the most beautiful course on Machine learning. To all those thinking of getting in ML, Start you learning with the must-have course. Thanks Andrew Ng and Coursera for this amazing course.

Filter by:

23,612 Reviews

By Anil Lahoti

Mar 26, 2019

I have used algorithms through out my career but the notion that machines can learn was a bit vague for me until I took this course. The fact that well designed algorithms can delve deep into the vector space and hyperplanes and tease out non-linear relationships is mind boggling, but that is what they can do faster than humans. I would recommend this course to any future scientist so they can leverage new knowledge and avoid pitfalls of AI.

By Ashutosh Mishra

Mar 26, 2019

.

By mohammad hasan

Mar 26, 2019

its good

its learning algorithms but not learn good implementation

By Venkata Rama Mahendra Vankadara

Mar 26, 2019

Awesome Course.... Dealt perfectly with real time examples. Explained very well with the help of Mathematics. My sincere thanks to Mr Andrew.NG

By Yanggang Fang

Mar 26, 2019

Perfect!

By Petteri Toukoniitty

Mar 26, 2019

Excellent course with good programming excercises!

By Jinkui Hao

Mar 26, 2019

1.花了10多天的时间学完了,挺有成就感的,基本全程英文,虽然耗时一些但还是坚持下来了。这算是自己知识图谱的第一块拼图,很有纪念意义。完成之后才发现没有开始想象的困难,只要坚持去做,不会的就多花点时间,总是可以理解学会的。以上是对我个人感受。

2.另外说一下这门课程本身,应该说是讲的很好了,对于我这种几乎零基础的人来说,没有遇到太大的困难,感谢老师。

By Shubham Srivastava

Mar 26, 2019

Great course

By Devesh Kumar Garg

Mar 26, 2019

Best teacher.

By li xiaoyan

Mar 26, 2019

Great class and very helpful!