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學生對 斯坦福大学 提供的 机器学习 的評價和反饋

4.9
121,268 個評分
29,773 個審閱

課程概述

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....

熱門審閱

HS

Mar 03, 2018

My first and the most beautiful course on Machine learning. To all those thinking of getting in ML, Start you learning with the must-have course. Thanks Andrew Ng and Coursera for this amazing course.

ML

Aug 19, 2017

Very helpful and easy to learn. The quiz and programming assignments are well designed and very useful. Thank Prof. Andrew Ng and coursera and the ones who share their problems and ideas in the forum.

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27801 - 机器学习 的 27825 個評論(共 28,895 個)

創建者 Roberto M

Aug 27, 2017

This course is quit hard, specially during the Programming Assignments. Some quizzes were hard, but for the most part I will recommend this course to everyone that will like to learn Machine Learning.

創建者 Francisco D G

Feb 21, 2018

Very good, but the feedback on quizz tests did not work at all from me (from any platform)

創建者 Roberto G R

Jan 02, 2018

Very useful introductory course!

創建者 Alex S

Aug 24, 2017

Great, just some of the assignments are a bit frustrating simply because you aren't given clear instructions on what you are supposed to do. Getting assistance with code is also near impossible for some questions. Overall I learned a lot and enjoyed the class, but there is still a bit of room for improvement I think.

創建者 Piyush U

Oct 27, 2017

It was a very brief and good way to teach the ML course.

創建者 Daumantas B

Sep 13, 2017

A nice introductory course with broad coverage. Not sure how good for a complete beginner; with a MSc in Statistics and PhD in Economics with a heavy doze of econometrics, it was just fine. The professor is friendly and encouraging. The quizzes really test you even though they contain just multiple choice questions. The programming assignments are useful for better understanding the algorithms, although there is still some way to go before you can really apply them in the wild. Four stars easily.

創建者 George M

Aug 09, 2017

I really like the course and Professor Ng makes the subject approachable and easy to understand. However the Quiz Questions with "check all that apply" responses always trump me and I get less than 20% complete. These "check all that apply" questions really discourage me from going on because I feel inadequate 'stupid' and have to constantly check my work rather than demonstrate any mastery of the subject.

創建者 Sky W

Oct 14, 2017

Overall very good, however this youtube video https://www.youtube.com/watch?v=aircAruvnKk by 3Blue1Brown on Neural Networks made some features about neural networks at lot clearer. Specifically, in understanding what the hidden layers actually do. Including a similar introductory video to that topic would have helped me.

創建者 sujay p

Oct 17, 2017

Thanks a lot to Coursera , and Andrew sir for making this course very easy to understand

創建者 Paul S

Sep 20, 2017

I learned a lot in this course. I am surprised that so much known errata has been left as is. The forum resources catch most but not all of it. There is room for improvement.

創建者 Yogesh A

Sep 23, 2017

Excellent way to learn Machine Learning!

創建者 Alain S

Nov 04, 2017

great intro even for the one who just want to get an idea of what ML is all about and what are the basics knowledge many current companies are using to build their products

創建者 Gillian B

Sep 17, 2017

Thoroughly enjoyed this course - it was my first Coursera course. I have a degree in Pure Maths and IT, but I graduated back in 1995 so it's over 20 years since I did anything academic. This brought so much back and introduced me to ML which is absolutely fascinating and I intend to study more on ML e.g. try some of the dataset problems on Kaggle. I did this course purely for recreation and got through it in just over a month (I work full-time). I liked that I could work at my own pace and get ahead so that if other commitments took over, I could put it aside for awhile and still be on track. I have knocked off one start because: I would have liked more practice questions/exercises to cement some things (it was easy to forget what some of the variables stood for in some of the longer equations; the audio quality was not great. That said, I realise that this was the first MOOC from Coursera, so I expect that's been improved in other courses since.

創建者 Brendan A

Oct 05, 2017

This course offers a very clear path towards understanding machine learning. By the end of the course I understood high-level ML concepts and am now well-equipped to begin learning further. I only say 4/5 because there are some glitches in the course around the timing of the in-video quizzes, and some of the videos need to be edited. Otherwise fantastic!

創建者 Sangamesh V K

Mar 04, 2018

Except for the last quiz which contained irrelevant/naive questions, Course was amazing.

創建者 Onur G

Sep 15, 2017

So far, so good.

創建者 Christian F

Oct 07, 2017

A lot of maths and some weeks really hard but definately worth it, very interesting!

創建者 Kristiaan K

Feb 05, 2018

Clearly taught, good level, sufficient suppor

創建者 新新新用户

May 14, 2018

This course is very useful.But there are some shortcomings.The last few weeks have no summary notes.There is no code exercise in the last two weeks.Anyway, thank you very much.

創建者 Gege R

Nov 04, 2017

J'ai appris beaucoup de choses en si peu de temps ! Thanks !

創建者 Carlos R

Jan 27, 2018

Very nice course. Maybe it misses some more practical examples, but I've learned a lot :)

創建者 Saikishore K

Jan 15, 2018

Very good one for updating skills

創建者 Gerrit S

Apr 09, 2018

Hello, first of all a great job for all of those that were involved to create this course. To get this all done practically (quizes, excercises, video's, lectures and so on), it's a very great job and a thank you is going out to all people involved to archive this.

The most interested weeks were the weeks from week 1 to week 5. And then also the last two weeks namely 10 and 11. Some weeks (weeks in between 5 and 10) are in my opinion dedicated courses on Eg: The supported vector machine. To complicated in my opinion for one week.

By following this course I have certainly got the basics of machine learning and looking forward to start with the more in dept courses of Deep Learning. So I will be back very soon when taking up one of the advance courses of Deep Learning.

創建者 Ashwini S E

May 31, 2018

Great course , would've been better if it was done in python!

創建者 Aaron S

Jan 04, 2018

The course was very interesting, well thought out, and well taught. The script that accompanies the videos can be wildly inaccurate, so it would be good to have the ability to crowd-source corrections.