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Kursteilnehmer-Bewertung und -Feedback für Maschinelles Lernen von Stanford University

119,195 Bewertungen
29,267 Bewertungen

Über den Kurs

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....



Mar 31, 2018

Perhaps the greatest instructor and the greatest course, I enjoyed it so much I had continued to do it in between my exams and looking forward fto start or deeplearning,ai specialization in a few days


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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27926 - 27950 von 28,386 Bewertungen für Maschinelles Lernen


Jul 14, 2019

The way the course was designed to help students learn so much in such less duration with given simplicity is just phenomenal.

von Jagadeesan R

Jul 15, 2019

Very helpful in learning optimization algorithms which challenges the data processing and prediction

von Vincent k

Jul 15, 2019

very interesting class but the sound is very bad

von Rahul P

Jul 15, 2019

I think week 8 and week 9 should be better explained, its going too fast. I would have also liked to learn the mathematics behind the algorithms although it was not part of the course. Thank you

von MOHD T

Jul 17, 2019

No books mentioned

von shail

Jul 17, 2019

All time best course and its study material is very helpfull and 100% improvement of skills.

Big Thanks.

Andrew Sir

and coursera also.

von Chris D

Jul 16, 2019

As others have pointed out, this is a basic course that shies away from math and programming. If I could change anything about the course, it would be to emphasize the importance of vectorization and minimize the teaching of imperative programming (the latter being out-of-scope). How could a particular matrix operation work, procedurally? Well, that should be communicated as out-of-scope or perhaps relegated to a single lesson/assignment partway through the course.

That said, the course presented a solid overview of the different aspects of ML. I don't regret having taken it, and will in fact seek out other courses taught by Andrew Ng. Thanks, Andrew!

von Akash k

Jul 18, 2019

Course is awesome

von Siu L C

Jul 18, 2019

very comprehensive and practical course!

von Balaganabathy K

Jul 16, 2019

Excellent introduction to the basics of machine learning. This course builds a strong foundation to move on into more advanced topics.

von Jed Z

Jul 16, 2019

The video and the audio are not clear enough, but the content there is really great.

von Arnaud B

Jul 19, 2019

Writing code is much more difficult than following the videos. You could feel a bit lost sometimes. But it is worth the effort!

von Komati G N S T

Jul 21, 2019

Overall the course is great and the instructor is awesome. Machine learning is fascinating and I now feel like I have a good foundation. A few minor comments: some of the projects had too much helper code where the student only needed to fill in a portion of the algorithm. I would have preferred to have worked through more of the code. Also, there were a few times when the slides didn't contain the complete equations so it was difficult to piece it all together when writing the code. Lastly, I wish that there was more coverage on vectorized solutions for the algorithms.

von Shashankh C

Jul 19, 2019

The course is definitely exceptional in its scope and accessibility. Beginners without knowledge of math would get practically relevant skills and students with a good background would be able to experience the joy of deriving the important equations. Andrew Ng manages to traverse the fine line of balance that nobody is bored, or feeling helpless. The only main problem I had was the audio quality - it is poor, and in many places, Professor Ng is either inaudible, or too loud, or unclear ... Since this is an old course, it is acceptable. However, I would have preferred a remastered version with less of these problems.

von Mohammad E

Jul 20, 2019

During the first weeks, there is a possibility to review the contents of each lesson in a text file immediately after watching the relevant video. But, in the last weeks there is no text files to review at all which was really annoying.

von Abishek C

Jul 21, 2019

A comprehensive course on Machine Learning (ML), starting with the fundamentals and building upon the various concepts of supervised and unsupervised ML. The course also offers real world tips on how to make sure the time spent designing and implementing ML projects are worthwhile by elaborating rigorous analysis techniques such as 'learning curves', 'ceiling analysis' etc. Some prior experience of general programming and grasp of linear algebra (matrices) would make the assignments easier to do. Some of the assignments could do with a bit more clarity (rewrite) to make things clearer. Don't let this put you off though, help is on hand via the forums for those who find it a bit tricky.

I'd recommend this course to anyone looking to understand what ML is all about whether it be out of just curiosity or indeed to pursue a career in ML.

von Rakshit K T

Jul 19, 2019

This course covered most of the theortical part of machine learning but there should be some implementation details also.

von Christopher P

Jul 19, 2019

Very good on all the fundamentals. A good bit tricky with the matrix algebra minutia and working in Octave.

von Abhishek S

Jul 20, 2019

More of the theory than practical , However you will understand the basic of machine learning very clearly. It is not enough to start working on Machine learning in 2019.Good course to start with Machine learning. I would like to thank Andrew NG.

von Murali T S B

Jul 21, 2019

A tough course for beginners but worth it. I just wish Prof. Andrew did not trivialize that equations need not be understood. If you're reading this, you should know that they require work to understand to be able to code well.

von A A

Jul 21, 2019

it's a pretty good course, the lectures are very well done, the professor is very considerate of his students' time, the quizes are great, only the programming assignments could have been designed better to be meatier, but they're still good and solidify the ideas taught in the lectures. The professor makes it a point to explain why he has us use octave, we followed his lead, but using it, although being not hard, is a foreign tool that we had to learn. in summary the professor is great and the class is worth your time

von Santarelli R

Jul 22, 2019

Great course for beginner in machine learning, with a lot of practical tips to start writing code.

von Guy D

Jul 22, 2019

Generally a great hands on course - the first few weeks gave me various tools to be build my own ML system, mainly neural network implementation and improving. The last few weeks were too much theoretical and too much general to comprehend in such short sessions... I would replace them with more hands on topics such as evolution ML, etc. Thank you Andrew Ng.

von Aswith k c

Jul 23, 2019

Great course and recomended course for beginers

von Armaan P

Jul 24, 2019

Python should have been preferred for programming exercises, as it's has large industrial application.