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

4.9
114,658 Bewertungen
28,183 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....

Top-Bewertungen

SB

Sep 27, 2018

One of the best course at Coursera, the content are very well versed, assignments and quiz are quite challenging and good, Andrew is one of the best guide we could have in our side.\n\nThanks Coursera

RR

May 19, 2019

This is the best course I have ever taken. Andrew is a very good teacher and he makes even the most difficult things understandable.\n\nA big thank you for spending so many hours creating this course.

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25926 - 25950 von 27,309 Bewertungen für Maschinelles Lernen

von Pradeep K

Feb 13, 2016

It's a good start for those who want to start explore Data Science. If more(Optional) concepts were included It would really be nice for those who already know a bit of Machine Learning.

von sara k

Sep 19, 2017

the programming assignments were a bit hard, I have spent 3 weeks on one of the assignments, but overall the course is amazing

von Christoph G

Feb 17, 2016

Very good lecture. The assignments could be a bit more difficult/complex.

von Juan C

Mar 10, 2016

I missed something more about the last lessons. Some achievements like in the previous.

von marvin z

Sep 23, 2017

It is a pretty nice course for those guys who are interested in machine learning!

von Vaibhav V

Jul 11, 2018

Mr. Andrew Ng explain complex things with utter simplicity. This course is really a great head start for anyone to learn Machine Learning from scratch.I specially enjoyed solving the Quizzes and Programming exercises.Forum and support also proved to be very helpful.Overall the course was simply amazing.I would have given five stars if they have also included some guidance on where a beginner can go next with this knowledge to build a professional career in Machine Learning.

von Raj V

Jul 10, 2018

I really enjoyed the course. It put together all the relevant material in a cogent orderly manner. Great jobThe notation was a little tough. The subscript and superscripts (combined with the matrix notation ) required patient unravellingThe course is missing some mathematical rigor. I appreciate that it cannot be covered in the class itself, it might be useful to have it in the notes. One example that come to mind are a. Whether to divide by m or m-1 when estimating the standard deviation. A complete group project is probably a good idea

von Vipul G

Jul 10, 2018

Although the subject is a bit technical but the videos are quite structured and easy to understand. Necessary examples are in place and pauses are taken to make the audience is able to grasp. Interim exercises are interesting too.

von Shaunak P

Jul 09, 2018

Fantastic course to learn the basics of Machine Learning. This course mainly teaches you the motivation, the math and the structure of various types of machine learning algorithms, but does not focus on the implementation details. If you're looking for a more hands-on approach, then this may not be better suited to you. The examples are a bit old, as is the material, but are good enough for explaining the problems. Having said that, this is a good course to start your machine learning journey with!

von Eliton L S P

May 27, 2016

well explained, detailed

von Rhýthm K

Jun 14, 2016

the course is very easy to understand and implement.

von yettella s p r

Jun 18, 2018

It gives a boost and motivates you to learn machine learning. Also some complicated topics are not explained in detail due to the time constraint. But this is definitely a kick start for your future of AI and machine learning

von Harini D

Aug 31, 2016

Great Course for beginners!

von Vladislav Z

Jan 29, 2017

Almost perfect for beginners. There are some glitches in some assignments but I hope that they will be fixed.

von harsh T

Dec 04, 2017

A perfect start in the growing world of machine learning. Covers all the neccessary topics, with taking due care of the conventions and industry requirements.

von Ido N

Oct 23, 2017

Great introduction to machine learning, and it gets you through all the concepts, ideas and terms nicely. I feel like this course is perfect for people who manage tech teams and people who wants to take their first step into the subject. Having said that, after completing the course I don't feel like I can go and build my machine learning system and that I should learn another libraries and toolkits in order to apply what I learned in real world programming.

von Morin D

Jan 27, 2017

The course is really great to understand machine learning from scratch! Videos are really instructive and the many quizzes and exercices are well thought. The only (small) inconvenient is that sometimes the learner spend a lot of times explaining some basic concepts making the video a little long. Still, I highly recommend this class to anyone who wants to learn about machine learning!

von Romain T

Sep 10, 2015

Excellent course !

Good choice of topics, great explanations, I liked that there are many practical tips.

I would have liked: less guided programming exercises (the solution was almost given in the comments in the file to write) and larger (the student has to write only small bits of the overall project).

I would also have liked recommended links or reading whenever a proof or an explanation of a mathematical result was skipped. I think the choice of what was skipped as too detailed for an intro was good, but would have been nice to have pointers for students who wanted to explore more.

von ashwani j

Oct 12, 2015

The course is very good and Prof NG's explanation is also perfect.

There could have been some ungraded examples to practice different type of scenarios, to help us understand more.

von Honey

Apr 19, 2016

great Lectures

von Evaldas K

Aug 04, 2017

Almost perfect for beginner but some topics were rushed and were not clear at the end of week.

von Michał Z

Sep 09, 2016

Really nice course, in my opinion it could be some more stuff about how really SVM works,

but it's great, anyway.

von Aditya

Jan 17, 2018

Excellent course for learning the core of machine learning using mathematics.

von JeongHoon C

Feb 01, 2017

Very good overview of machine learning. Doesn't go into detailed mathematical construction of the methods/techniques but the course does provide you with the overall/big ideas used in machine learning. If you are completely new to machine learning, definitely take this course! If you're from a different background (math/stat etc), this course will provide you with a good transition into machine learning.

von MrBox

Sep 26, 2015

It is very suitable for those who have no background involving machine learning, this lecture is very basic but practical and essential.