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

114,559 Bewertungen
28,160 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....



Jun 15, 2016

Excellent starting course on machine learning. Beats any of the so called programming books on ML. Highly recommend this as a starting point for anyone wishing to be a ML programmer or data scientist.


Nov 11, 2017

Great teaching style , Presentation is lucid, Assignments are at right difficulty level for the beginners to get an under the hood understanding without getting bogged down by the superfluous details.

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25876 - 25900 von 27,295 Bewertungen für Maschinelles Lernen

von Semako A

Jun 21, 2017

Quite interesting and instructive. Tutorials also help a lot. On the negative side, some videos have to be edited to remove "rephrased sections".

von Piotr W

Oct 28, 2016

Très intéressant et fait une bonne introduction. Les exercices sont bien trop guidés voir pré-programmé pour les élèves.

von Nishant G

Feb 23, 2017

Good Concept wise

von Pritish Y

Sep 17, 2015

I am sad to see after accomplishing 11 weeks course there wasn't any certificate given.

von Marios F

Apr 29, 2017

Great course delineating all the fundamental principles. Some parts of it maybe a bit too easy for people with decent linear algebra knowledge but definitely a comprehensive and worthwhile introduction in the exciting topic of Machine Learning. I'm definitely motivated to learn more !

von Sharjeel L

Nov 04, 2017

Great class. Thank you Andrew. I would love to enroll for a follow up class where we can build a project from ground up maybe using R this time.

von Malhar K

Jun 18, 2017

The course taught the mathematics behind most of the algorithms and now moving forward, I will not just be using some library function but will have a good understanding of what it does under the hood. Also, the parts of the course that stress on evaluation of the algorithms and areas to focus to improve accuracy, debugging and prioritizing tasks is great. I would have loved to have more programming assignments in the course. Also, the assignments include completing code with the structure already provided. Looking back, if there would have been some I needed to do entirely, I feel it would make me better equipped for further projects in this domain. Thank you!

von Ayushi B

Aug 22, 2017

Missing modules for Decision Trees, Naive Bayes and more about Deep Learning.

von Rishabh J

Feb 22, 2018

Good course for beginners. Need more practical problems in the course so that we can know how to apply in real life problems.

von rajdeep p

May 02, 2017

A good introductory course into the realm of machine learning. This course has a very well constructed, application oriented content.

von Inês M

Nov 17, 2017

Great course to learn the theory behind ML.

von Zack W

Sep 28, 2016

Very interesting subject matter, and I learned a lot. My biggest complaint is that many of the programming exercises have errors in them that haven't been fixed, despite this course having been running for years. This always left me wondering if an incorrect output was an error on my part, or an error in the provided code. Still, I thoroughly enjoyed the course as a whole and would definitely recommend it to anyone looking for a foundation in machine learning.

von Mark W

Jul 22, 2017

Solid course, could do with having tidier readings/lecture notes but the videos are fantastic. Programming assignments worthwhile if a little basic.

von Srinivas A N

Mar 17, 2018

Very good explanation of the basics. Even a novice to Machine learning, could follow and understand easily. One things to improve this further would be to explain each superscript / subscript used in the mathematical equations, so that it is clear to the learner. There were also a few errors in the initial videos, but there are clarified in the forums.

von Gabriel O C

Jul 05, 2016

I thought there was too much math and coding for my taste. But overall, the course is great.

von vinamer

May 28, 2017

It is the best course any beginner can find in the field of Machine Learning. It starts with the most basic concepts and gradually teaches some very important aspects of the field.

The only con is that the quality of video and sound is bad at times.

von Jerick E Ó S

Oct 20, 2015

Pretty cool!

von Ashish S

Dec 12, 2015

Just awesome!

von Ash

May 03, 2016

The only reason that it does not get 5 star is due to the fact that the uploading of assignment is really confusing. The code is not uploaded till the solution is right which creates confusion whether the code is wrong or the upload mechanism is wrong

von Arturo D C

Feb 14, 2016

Good but sometimes pretty fast.

von tony c

Sep 19, 2017

really interesting even if very technical

von Peter H N

Apr 27, 2016

Course provided very good general overview of ML, but did not go in-depth into mathematics behind many of algorithms discussed.

von Dirk E

Nov 17, 2017

Very usefull introduction to ML with background in the mathematics behind it and tips on how to build good ML applicatoins. It misses some of the latest, state of the art techniques in ML.

von Jude

May 31, 2016


von Alessandro C

Dec 19, 2016

Audio quality low, sometime is difficult to understand what it is said.

The course, anyway, is a lot of value.