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Machine Learning, Stanford University

4.9
90,972 ratings
23,190 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 AA

Nov 11, 2017

Great teaching style , Presentation is lucid, Assignments are at right difficulty level for the beginners to get an under the hood understanding without getting bogged down by the superfluous details.

By OK

Apr 18, 2018

You need to know, what do you want to get out of this course. It gives you a lot of information, but be prepared to work hard with linear algeabra and make efforts to compute things in Mathlab/Octave.

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22,346 Reviews

By Sérgio Henrique Nilson Backes

Jan 22, 2019

I have found this course very satisfying, and also it provided nice challenges in the programing excercises. Professor Ng is very focused on the practical results and the real life application of the concepts, which I found very straight forward and efficient. It was my first (professional and serious) online course and I am very happy with the final results as I feel confident for proceeding and applying the techniques in my professional life. Thanks to Professor Andrew Ng for such dedication. I have dedicated some time to volunteer in translating the course to Brazilian Portugueese as a form of retribution for such a nice course.

By

Jan 21, 2019

wonderful course

By Sudeep Kurian

Jan 21, 2019

This course is really good in terms of explaining machine learning concepts in a very simple manner. It helped me understand how an algorithm really works instead of explaining some python libraries. What I didn't like was coding on octave. Apart from that, I loved this course.

By Adrielle Santana

Jan 21, 2019

Muito didático. Gostei muito das explicações e dos exemplos.

By Vignesh

Jan 21, 2019

A must take course for every starting in ml field

By Jawsem Al Hashash

Jan 21, 2019

Andrew Ng teaching is great! He breaks complex concepts into easier to consume chunks. He not only explains how to implement specific machine learning algorithms, but how to recognize when there are issues with the models you create and how to address them.

By Prashanth Duvvada

Jan 21, 2019

One of the most amazing and exciting classes. A must for a beginner and surely recommended for one who wants to start Machine Learning. Wonderfully taught by Prof. Andrew.

By Prateek Joshi

Jan 21, 2019

Exceptional. Best course to start learning Machine Learning! Only one grouse though, the exercises are in Matlab and not in python.

By min jiang

Jan 21, 2019

great tutorial, back propagation could be more organized though

By Joel Cantero Priego

Jan 21, 2019

One of the best Machine Learning courses ever. So proud of it.