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机器学习, 斯坦福大学

4.9
99,661 个评分
24,910 个审阅

课程信息

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....

热门审阅

创建者 JS

Jun 17, 2017

Everything is taught from basics, which makes this course very accessible- still requires effort, however will leave you with real confidence and understanding of subjects covered. Great teacher too..

创建者 DW

Feb 20, 2016

Fantastic intro to the fundamentals of machine learning. If you want to take your understanding of machine learning concepts beyond "model.fit(X, Y), model.predict(X)" then this is the course for you.

筛选依据:

24,047 个审阅

创建者 Shireesh Potnuru

Apr 20, 2019

Good course for Beginners

创建者 Tarek Naous

Apr 20, 2019

Excellent

创建者 Badrinath Nagarajan

Apr 20, 2019

Excellent coverage of key concepts of machine learning and algorithms that were well supplemented by exercises. Truly enjoyed the course!

创建者 Mauricio Acuna Valdes

Apr 20, 2019

Very good introduction and a little bit more to machine learning. A lot of concepts, very well explained. Very good teacher

创建者 wansijie

Apr 20, 2019

excellent course, hope i can apply this meachine learning on my job

创建者 Anas BARIK

Apr 19, 2019

best ML existing course

创建者 Nguyễn Việt Thành

Apr 19, 2019

good

创建者 Rajpal singh Dodiya

Apr 19, 2019

This course is really good and a step towards the real world of machine learning and it's applications,

Thanks to coursera for such course.

创建者 Shankar Muthusami

Apr 19, 2019

The Best Tutorial for ML. Thank you so much Andrew Ng.

创建者 Neo

Apr 19, 2019

pretty good!