Chevron Left
Zurück zu Maschinelles Lernen

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

114,201 Bewertungen
28,078 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....



Apr 22, 2017

Very good coverage of different supervised and unsupervised algorithms, and lots of practical insights around implementation. All the explanations provided helped to understand the concepts very well.


Oct 31, 2017

Great overview, enough details to have a good understanding of why the techniques work well. Especially appreciated the practical advice regarding debugging, algorithm evaluation and ceiling analysis.

Filtern nach:

26576 - 26600 von 27,196 Bewertungen für Maschinelles Lernen

von Gokul G

Jan 16, 2018

This course is a very well structured for someone to give complete understanding of how machine learning algorithms are designed and executed

von Harshal K

Mar 15, 2018

It is very helpful for a person who wants a proper explanation on machine learning because this covers all the important algorithms from scratch. the tutor also explains everything clearly with no ambiguity in the audio. All in all this course will take the learner to the field of data science by introducing many concepts.

von Ambuj B

Feb 25, 2018

Just completed my first week of the course. The course is interactive and starts from the basics to go to the more complex problems, which makes it easy to understand.

Removing one point because there is sibilance in the audio and sometimes audio is hard to understand.

von Steve H

Nov 15, 2017

Great course, shame there are some errata that are only documented after the video - would be great if the video could be updated, or notes added as an overlay to the video.

von 朱祖伟

May 31, 2018

Will be better if new version with python is ready.

von Yash F

May 02, 2018

This is a nice course for beginners like me. It really helped me but I think assignments should be less descriptive and should be given to students to do the work.

von Venuder R s

Apr 16, 2018

Great course, very effective and easy to understand. Cons- It would be great if more algorithms are explained in case of unsupervised learning.

von ahmed a

May 07, 2018

First of all it was very fun,sometimes the videos were too long ,but it was absolutely useful

This course was really helpful for me specially in understanding the concepts,I have seen a lot of courses and when I forgot how an algorithm is working, I return to watch the videos again

The study notes after each video were very helpful, I'm really sad that they weren't there in the last weeks , I hope you will add them , Thanks really for this course and teaching me

von Kshitij L

Mar 12, 2018

nice explanation of every aspect in machine learning with appropriate examples.

von Miguel A M

May 02, 2018


Ante todo, me parece un curso muy bueno y estoy muy contento de haberlo realizado, ha sido muy interesente. Soy analista informático y me dedico a esto.

Pienso que hay dos cosas a mejorar:

1- Me ha faltado algo para mi muy importante, no se ha explicado nada sobre cómo afecta la topología de la las redes neuronales en sus resultados. Parece que hay que "adivinar" mediante prueba y error el número de capas y de neuronas de la red.

2- La semana 11, con el OCR, creo que no aporta mucho.

von seenu

Feb 26, 2018

Very good.

von Jan v d L

Mar 09, 2018

Fantastic content!

Real in-depth and starts right back at the start...

Would get 5 stars if there was more information on the programming assignments...

von Sergey P

Feb 02, 2018

Too basic in the beginning. However, I do like the visual examples and if the course will keep chewing in such a details more complex subjects, that would be a great course!


Apr 21, 2018

Very Good. Student friendly. Difficult concepts explained with the simpliest way. One video lecture update may be required. Also some weeks overload can be moved to other weeks.

von Olivier P

May 13, 2018

Excellent course that I highly recommend. However, the sound quality could have been better so the 4 stars rating.

von Tomoki I

Mar 24, 2018

I am a Ph.D. student studying biology at a Japanese university. I decided to enroll this class because recently, many scientists apply machine-learning algorithms to various biological analysis.

Through this class, I learned a lot about machine-learning, and among them, the most worth thing is that what field should I learn more to apply ML. I learned basic knowledge to run ML by myself. This practical knowledge will help me to learn ML more.

There is just one thing to improve this course; Dr. Ng said that there are no problems even if we cannot understand the theories in some algorithms, but it will be helpful to tell us when it gets to be a problem if we cannot understand the basic mathematical theories.

I want to say thank you to Dr. Ng.

von Ryan M

Mar 30, 2018

Very good course, with plenty of useful information. In particular, I recommend the programming exercises. You really need to do them, in order to understand the material. My only "complaint" about the course is that it simplifies to the single vector description of the problems, but when you implement you need to vectorize the solutions. The vectorized solutions are actually easier, and clearer than the single vector descriptions in the videos! It would be helpful to have the vectorized approaches described in the videos directly. But the forums are helpful for that if you have any questions.

von Manish L

May 19, 2018

Though its an Old Videos but it is still worth it.

von Priyam n

Jul 14, 2018

Very good course.

von Shaun R

Jul 12, 2018

More hands on examples would have been good. Overall a great course

von Apoorv K

Jun 10, 2018

This course is fantastic to learn core fundamentals of ML. It shows you a high overview of the ML land. However, do not expect that this course will make you a fulltime expert. This is an introduction and solid stepping stone into AI.

von Ander

Jun 07, 2018

Un curso muy interesante, muy intenso que conlleva mucho trabajo. Merece la pena.

von Evan D

May 14, 2018

Good overview of machine-learning basics. Don't expect to have an intimate or working knowledge of the algorithms after this course, but expect to develop some intuition as well as awareness of common pitfalls. The programming assignments often felt more like an exercise in vectorizing code rather than reinforcing algorithmic understanding. All in all, though, good course for establishing the fundamentals, and I now feel confident to make further forays into ML.

von Sundaram M

May 19, 2018

Good for learning basics


Mar 07, 2016

loved it,really helpful for my project