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Avis et commentaires pour d'étudiants pour Apprentissage automatique par Université de Stanford

4.9
étoiles
126,646 évaluations
31,044 avis

À propos du cours

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....

Meilleurs avis

AD

Apr 22, 2017

Very good coverage of different supervised and unsupervised algorithms, and lots of practical insights around implementation. All the explanations provided helped to understand the concepts very well.

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.

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126 - 150 sur 10,000 Avis pour Apprentissage automatique

par Jorge L R C

Jun 05, 2019

Even being for a "old" course, it has the very best ground of concepts and techniques of Machine Learning. I am very much satisfied and have learned a lot.

par Danny F B L

Feb 12, 2020

This is definitively an excellent course for beginners. I am graceful with Andrew Ng for the dedication he gave for building this course. Congratulations.

par Ajay T

Jul 29, 2019

Excellent course. Discussion forum help from the mentors was super in the first half of the course but towards the end the mentors did not participate

par Sohan J S

Jun 06, 2019

It was an amazing experience in learning Machine learning. I learnt a lot from this course. I thank the instructor, Prof. Andrew.

par Anish K A

Feb 22, 2019

Excellent course. I am not an expert in mathematics, but this course gives me a very good understanding of ML and algorithms.

par Joydeep S

Nov 07, 2018

Excellent course. Anyone interested in Machine Learning should definitely take this course. Thanks Andrew for making this.

par Cosmin V N

Aug 07, 2015

Amazing course. Complex topics explained in a way that anyone with a rudimentary understanding of math can follow.

par Naveen K

Sep 19, 2019

One of the best Machine learning course :) Andrew's way of teaching is really a masterpiece :) Thank you Coursera

par Luka B

Jan 30, 2019

Great course, only a bit updated. Would be wonderfu if there was an update (or additional week of two) for 2019!

par Mai S

Jun 06, 2019

Thanks Andrew for this informative course. I am looking forward to taking deep learning specialize as well.

par Anton S

Mar 21, 2019

It's a good way to get an understanding of machine learining principles and to improve your English.

par dinh

Dec 15, 2018

Great course on Machine Learning. I learned a lot!

Thanks to Professor Andrew NG and all the mentors.

par YuShih C

Jan 04, 2019

Great introductory course for Machine Learning using MATLAB/Octave. Highly recommended.

par syh

Feb 09, 2020

从机器学习新人、小白,通过这门课程充分理解了机器学习的原理,掌握了一些机器学习的技巧,并能够根据学到的知识,举一反三,应用到更复杂的机器学习算法的理解中。总而言之受益匪浅。

par runner_yang

Jul 25, 2019

Thank you sincerely! I have learned a lot through this course. I love Ng and coursera!

par 赵子皓

Feb 10, 2020

8个exercise出的非常好,程序中给的note和hint有助于理解计算过程、加深记忆。

吴恩达老师英语很有亲和力,对于我这样的英语听力一般的人来说非常友好

par Mohammed R

Aug 07, 2015

the audio is sometimes noisy, but everything else is perfect, thanks a lot

par Erasmo G M S

Oct 02, 2018

Great!, this was my first aproach to machine learning and I learned a lot

par 王奇

Aug 07, 2015

吴恩达老师的这门课帮助无数学生了解了什么是机器学习,虽然有时候作业会很没有头绪但是通过努力研究一般都能做出来,而且满满的成就感。。感谢andrew

par MRINAL G

Jan 17, 2020

Best Online Machine Learning Course available. Excellent tutor.

par zhiyiwang

Sep 16, 2019

Very understandable and straightforward class for beginners.

par Donny I

Dec 15, 2019

very usefull to study the fundamental of machine learning

par Dhruva

Jan 02, 2020

A exceptionally great course for beginners in the field.

par Sasker G

Jun 05, 2019

Great course to understand how machine learning works!

par Mohammed M

Apr 03, 2019

I learned a lot from this course, very recommended