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Вернуться к Машинное обучение

Отзывы учащихся о курсе Машинное обучение от партнера Стэнфордский университет

4.9
звезд
Оценки: 158,302
•
Рецензии: 40,531

О 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

QP
24 июня 2018 г.

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.

VB
2 окт. 2016 г.

Everything is great about this course. Dr. Ng dumbs is it down with the complex math involved. He explained everything clearly, slowly and softly. Now I can say I know something about Machine Learning

Фильтр по:

251–275 из 10,000 отзывов о курсе Машинное обучение

автор: Maurya R

•
3 июня 2020 г.

It is a very good course for Beginners. It's worth it!

автор: Sasker G

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5 июня 2019 г.

Great course to understand how machine learning works!

автор: Mohammed M

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3 апр. 2019 г.

I learned a lot from this course, very recommended

автор: Yuhang T

•
17 янв. 2020 г.

thank you, I have learned a lot from this class.

автор: 个a

•
2 апр. 2019 г.

excellent class.worth your time and thank you ng

автор: Roei B

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17 янв. 2019 г.

10/10. Andrew is an amazing teacher. Thanks!

автор: zhaoyi

•
2 янв. 2020 г.

Very good intro course to machine learning

автор: Zilin L

•
7 июня 2019 г.

几乎没有数学要求，老少咸宜。

编程作业设计非常用心，专注于让学生完成核心人物。

好评！

автор: Hamed B

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5 июня 2019 г.

THE BEST COURSE IN ML BY FARRRRRRRR

автор: Bhanu p T

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1 янв. 2019 г.

Loved it. Easy and Excellent Course

автор: Luu V L

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5 авг. 2020 г.

best ML course in the world !!

автор: Jaspinder S V

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8 авг. 2015 г.

Awesome course for beginners.

автор: Mulat Y C

•
14 февр. 2020 г.

Machine Learning

Data Science

автор: Mewada A J

•
5 авг. 2020 г.

best experience of learning

автор: 梁驰

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8 февр. 2020 г.

喜欢吴恩达教授的课，讲的非常的好！教授很谦虚！赞赞赞！

автор: chandan k

•
6 июня 2019 г.

Great course to study!

автор: Eugene M

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4 янв. 2019 г.

Very useful course!

автор: Joy F Y

•
7 авг. 2015 г.

It's very useful

автор: Pavel K

•
6 июня 2019 г.

A great course.

автор: Hacker O

•
17 июня 2019 г.

very good!!

автор: Stephen M

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5 июня 2019 г.

Very useful

автор: ylfgd

•
6 июня 2019 г.

very good

автор: Thierry L

•
4 янв. 2019 г.

Excellent

автор: Saiful A

•
7 авг. 2015 г.

Very Nice

автор: Vivek K

•
13 дек. 2018 г.

Awsome

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