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Machine Learning, Stanford University

4.9
Оценки: 87,541
Рецензии: 22,456

Об этом курсе

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....

Лучшие рецензии

автор: JP

Oct 25, 2016

Great course. A progressive discovery of the maths inner to the learning algorithms. This course gives that insight many ML practitioners don't have and is so important for making real use cases work.

автор: MN

Jun 15, 2016

Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.

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Рецензии: 21,613

автор: Rajeev Aggarwal

Dec 12, 2018

Simply Awesome ! Very thorough contents and Andrew Ng explained the concepts very clearly.

автор: 可可

Dec 12, 2018

Perfect lecture!

автор: Manjunath GK

Dec 12, 2018

Best place to start Machine Learning for Beginners for easy and effective understanding

автор: Arjun Sharma

Dec 12, 2018

Great Knowledge provided for Machine Learning

автор: Kevin Ruiz

Dec 12, 2018

Excellent introductory course

автор: MANIKANDAN RAMACHANDRAN

Dec 12, 2018

It is a wonderful experience to learn with Andrew, it's my pleasure to learn with him. Before that I thank coursera for giving my opportunity.

автор: Evrim Korkmaz Özay

Dec 11, 2018

Very clear, very-well explained. Masterpiece!

автор: Zhanluo Zhang

Dec 11, 2018

Very structured, very useful and easy to follow.

автор: Vil Varadhan

Dec 11, 2018

Excellent course. Thank you Dr. Andrew Ng. I enjoyed the course and I like your teaching approach very much. Thanks again

автор: Silvian Tofan

Dec 11, 2018

Exceptional!