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

4.9
111,327 Bewertungen
27,424 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

WZ

Apr 03, 2018

Very nice course,. Give a fundamental knowledge of machine learning in a clear, logic and easy-to-understand way. Suitable for those who has relatively weak background of math and statistics to learn.

CC

Jun 20, 2018

good course; just 2 suggestions: improve the skew data part (week 6) and furnish the formula to evaluate the number of iteration in the window from image dimension, window dimension and step (week 11)

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126 - 150 von 26,571 Bewertungen für Maschinelles Lernen

von Prakash M

Jul 14, 2019

This course is amazing and covers most of the ML algorithms. I really liked that this course has emphasized math behind each technique which helps to choose the best algorithm while solving a problem.

von Nils W

Mar 23, 2019

Great course, but the sound quality is quite bad.

von Mehdi E F

Mar 19, 2019

Very instructive course.

Thank you.

It would have been great to get an OCR exercice at the end.

von MAHESH Y

Apr 09, 2019

it is one of the best course for beginners in machine learning, the only thing it lacks is its python implementation. If there is the python implementation of this course then no other course is better than this one

von Saideep G

Apr 09, 2019

Very well made, well paced. Better than majority of college courses. Some errors do pop up midway through the course that should be addressed. It can be frustrating to push through these issues sometimes but they are the only thing keeping from 5 stars.

von Jerome T

Mar 06, 2019

I like the course very much. One point where it could be improved are the assignments: it is really nice to be guided and to have a big part of the programming prepared but the drawback is that many times I didn't feel in control of what was happening. For example, that was hard to know basic features of the implementation (is this data a row vector? a column vector?) since I didn't decide it. This leads me to spend quite some time on trying to fix simple problems. In short, I wish I had felt more "empowered" during the assignments.

von Mohd F

Nov 08, 2018

There is a lot to say about you Andrew sir but in few words - "Thank you very much for teaching us the ML concepts in such a beautiful manner "

von Doreen B

Jun 09, 2019

Well explained, at the end of this course you will understand the subject and hold coherent conversations about it. Matlab implementation relatively simple, maybe too much so. Highly recommended course.

von vamsi

Aug 05, 2019

Better upgrade from matlab to Python

von Eric S

Jun 06, 2018

This course needs to be severely updated and fixed. It is mostly kept alive by the amazing community of mentors, in particular, Tom Mosher. Without Tom, I would have gotten extremely frustrated with the weird quirks that come about during assignments. One important piece of advice: if you can do assignments in an Octave environment such as GNU Octave 4.0.3, I'd strongly recommend it (Althought it tends to crash ofter, so save, save, save!!!).

von Shitai Z

Nov 19, 2018

Too easy for people with background in machine learning. But would be a good introductory one if you have zero understanding in machine learning and want to change your career track.

von Manik j

Apr 06, 2019

This course is good but it cannot be able to clear the very basic knowledge of the student

von Mirko J R

Apr 02, 2019

Excellent lessons by Prof. Andrew Ng.

However very poor support. No answers from any mentor along lessons, you should resolve all doubts by yourself.

I had a problem with my ID verification, I was waiting for a long time without any responses.

Also, it's difficult to contact persons who could support you, I tried to contact someone but just found a Bot. Terrible support.

von トミー ペ

Feb 03, 2019

This course was very difficult, coming from a non-math/matlab background, but did teach me a heck ton about the world of machine learning, for which I am eternally grateful. Life got in the way big time, and it took a lot of time and energy to complete the programming exercises. There was also a lot I didn't understand, and I did wish there was maybe another week of getting used to certain concepts, particularly maths issues like double summing. I appreciate that this would complicate things though. I found that I am not geared towards the forums - my learning style involves conversation and not really experimenting on my own (which I can do once I understand a concept). As helpful as the mentors were, only relying on the forums with my time schedule meant that that taking this course dragged on longer than I would have liked. I also got a bit overwhelmed by the lack of centralised information. I know that it would require a complete overhaul to sort such out, but it did make looking up information time-consuming. Nevertheless, I am grateful for all that I learnt, and appreciate that I plunged into the deep end. I don't understand everything, and of course a little knowledge is a dangerous thing, but I know enough to know what to refer to should I ever need ML in my next job. Thank you.

von Jerome P

Mar 30, 2018

Good introduction course, giving an overview of machine learning algorithms and some methodology. Off course a lot can be added, but it's a good start for people with little to no knowledge or experience in this field. A few points that could be improved: I would like to have better material support for each section. Marked-up slides are not a great support for reviewing the different sections afterwards.

It would not hurt to provide a little bit more theoretical background and justification when covering the different algorithms. Andrew Ng almost apologizes when going into mathematical equations, but this is fundamental to machine learning.

quiz assignments are rather easy. They could be a little more challenging

I would rather have the programming assignment using R or python than Matlab.

But still a decent course overall I think.

von Subham B

Jul 24, 2019

This course is definitely not for beginners.

von Ivan Č

Feb 24, 2016

Certificate is expensive!

von Sergey K

Jan 24, 2016

Level of difficulty of lectures is not correspond with level of quizzes. In lectures they are talking about simple stuff and then in quizzes they ask you about details they didn't mentioned. You could deducts this information though. But this is exactly the main problem with this course - for quizzes you should deduct and learn by yourself so much stuff, that videos start to be not worth your time.

von Saleh a h

Jul 14, 2017

good so far

von Loftur e

Sep 17, 2018

Assignments are very messy.

von Rune F

Dec 18, 2016

Fairly good videos explaining the material, probably worth 4 starts. However, the written support material should be improved. IMHO the video should supplement the written material, i.e. it should be possible to learn the material only by reading. This is not the case, so frequent pausing of videos and making lots of notes is needed if one wants to commit this course to long-term memory.

von Goulven G

Jan 10, 2019

This course could be a nice introduction and overview of the Machine Learning field.

However, the video transcripts are TERRIBLE — do not attempt to find any traces of grammar in them ! After a while I figured there were lecture notes (seriously, why hiding them under Resources ??? some people don't want to or simply can't watch the videos), but some of them lack information needed for the quiz so for some sessions you still have to watch the videos or endure the transcripts anyway.

But MOST OF ALL, the course has an incredible number of (acknowledged) errors, sometimes critical for the programming assignments, and you have to dig into the forum and Resources Erratas to figure them. Given that this lecture has been online at least since 4 years and some people actually PAY FOR IT, I find this utterly disrespectful, hence my low rating.

Furthermore, note that the validation script for ex5 is too permissive : it accepts wrong linearRegCostFunction implementations, which makes the second part of the assignment quite painful to debug…

von Anton

May 11, 2018

Material of this course could be presented much deeper. Mr. Ng tries to avoid mathematical explanations.

von Samuel

Feb 19, 2018

The course is not for people with not mathematical backgrounds plus its using matlab.. these days R and Python are more used in the industry for ML. I found to this course via friends that said it's hard but very recommended.. i think there are easier courses online that can deliver the same concepts

.

von Hu L

Feb 14, 2018

Too easy and too slow