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Volver a Aprendizaje Automático

Aprendizaje Automático, Universidad de Stanford

4.9
100,074 calificaciones
24,983 revisiones

Acerca de este Curso

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....

Principales revisiones

por 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.

por EJ

Mar 27, 2018

Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.

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24,105 revisiones

por Shashank Gandhi

Apr 24, 2019

Excellent Course, Thank you so much for this!!

por Gaddam Akhileshwar reddy

Apr 24, 2019

Selecting questions and answering them is not so great.... we just want the basic idea.

por G Bala Kowsalya

Apr 24, 2019

Amazing course to understand underlying concepts of Machine Learning before starting kick-starting practical implementation. He makes every complex concept too to just a piece of cake. GREAT !

por Abhishek Verma

Apr 24, 2019

Very comprehensive coverage of all the aspects of the course.

por Yi Li

Apr 24, 2019

Great Class, Great Experience, Great Andrew, Valuable Cutting-edge Knowledge and Materials. This class has opened up my new erra and took me jump into the new page of life!

por Jean Lee

Apr 24, 2019

谢谢您!

thank you from my bottom of heart!

por Yaroslav Pugach

Apr 24, 2019

Great course! Probably the best I've ever taken. Everything is well explained and it was wonderful to see how Andrew predicts the questions which are likely to arise during the lecture. On the other hand, he knows how to ask right questions to make the brain work. Programming exercises are engaging and the guidelines are very thorough. I really loved about this course is that we studied where and how to apply the algorithms we learned to real-world problems. In fact, the programming assignments were real-world examples.

por Krayeu Uladzislau

Apr 23, 2019

Nice course, great step-by-step education.

por Carlos Lara

Apr 23, 2019

Though and challenging subject, but plowing along!

por Craig Pusczko

Apr 23, 2019

Good course for understanding the foundation learning algorithms of Machine Learning