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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

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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....



Feb 20, 2016

Fantastic intro to the fundamentals of machine learning. If you want to take your understanding of machine learning concepts beyond ", Y), model.predict(X)" then this is the course for you.


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.


27826 - 机器学习 的 27850 個評論(共 28,825 個)

創建者 Luke K

Apr 29, 2018

Andrew Ng's lectures are informative and well-structured, and homeworks do a decent job of reinforcing the learned material.

However, I feel that too much of the code was pre-written. I have put in considerable time to remedy this, but I feel that someone who has just completed the homeworks may not be fully confident starting any such problem from scratch.

創建者 David S

Jan 14, 2018

A good introduction to the domain. Decidedly light on important mathematics, but a few hours on Wikipedia and some ML blogs back-fill that information for the greatest part. It could probably use an update to reflect the actual state-of-the-art in 2018.

創建者 Dalia O

Jan 01, 2018

It is a great course if you dont have the basic tools for ML such as linear algebra.

創建者 Rishabh R

Feb 08, 2018

go for it if its your 1st course

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 Fortunatus O

May 29, 2018

knowledge of Machine Learning algorithms does not only help you solve personal real life problems but it can help you solve national and even international problems

創建者 Aditya G

Dec 11, 2017

Need more complex programming excersices

創建者 baoshu90

Feb 26, 2018

Meaningful and well organized course!

創建者 Raghavendra B R

May 05, 2018

This Course is well structured to provide basic understanding of the most widely used Machine Learning concepts and algorithms, It is the best Introductory course one can rely on to start their Machine Learning journey from.

創建者 Michael L

Dec 09, 2017

Good course overall but it loses a star because the assignment instructions are rather complicated, confusing and in a few cases send students completely in the wrong direction. Thankfully Tom Mosher has posted "Tutorials" (under Resources) that honour the vectorized approach shown in the lectures.

創建者 Bruno H

Jan 06, 2018

I really enjoyed this course and learned quite a lot. The exercises were pretty easy for me (I am in my mechanical engineering bachelor) and i would have liked it to go more in depth in terms of calculus. But there are other courses for that. The audio-quality could be better regarding this is a very popular course. Recommended for engineering students who want to get an overview of the applications of machine learning.

創建者 Ian B

Jan 04, 2018

Good class, though at times I felt like the quizzes were just notation exercises. The programming exercises were very insightful. I feel without a strong background in linear algebra this class will be extremely difficult.

創建者 Saikishore K

Jan 15, 2018

Very good one for updating skills

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.

創建者 Ashwini S E

May 31, 2018

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

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 Vishwanath G

Jan 05, 2018

I am very satisfied and found this course perfect for ML beginners. Thank you Coursera and Andrew NG.

創建者 André V

Jan 06, 2018

Not technical enough, and should have involved more mathematics (in my opinion). Apart from that, really great course!

創建者 suraj20041995

Mar 21, 2018

Its great for the beginners

創建者 Musa J

Aug 11, 2017

Andrew Ng well respected in the field. Lectures take clock time, & test are more of tests than learn along, though the field is a recipe today not analytic too. Some intuitive insight on distributions and cost y log h -(1-y) log(1-h) can help. SVM, Back forward prop are in here.

創建者 Lingjiao C

Aug 16, 2015

The course contains some fundamental concepts of machine learning. It is not very hard to accomplish the course.

創建者 Miguel C R

Dec 16, 2015


創建者 Diego D L

Jun 08, 2016

Nice introductory course on ML. A few typos in the slides could/should be corrected. Test submission (though Octave) should definitely be improved.

創建者 Clément G

Dec 14, 2015

The best online course i've ever attended. The explainations are crystal clear even for non-methematicians and the topic is widely covered ( No deep learning nor bayesian methods though). If only my former college teachers would've been half that good..

創建者 Davood M

Jan 14, 2016

It is great and the instructor is excellent.