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

119,262 Bewertungen
29,280 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....



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.


Oct 15, 2016

It's a good introduction - not too complicated and covers a wide range of topics. The programming exercises are well put together and significantly help understanding. The free Matlab license is nice.

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25851 - 25875 von 28,407 Bewertungen für Maschinelles Lernen

von David

Oct 29, 2019

Awesome course. Awesome syllabus. Awesome teacher. Thank you very much Andrew Ng.

von Yohei M

Oct 30, 2019

Andrew is a gifted lecturer and I feel extremely lucky to have taken this well-organised and challenging course on Machine Learning.

von Praful K

Oct 27, 2019

Excellent introduction to machine learning

von Paul C

Oct 28, 2019

Prof. Andrew Ng is a truly gifted educator! His ability to simplify complex concepts helped me gain an in-depth understanding of the more challenging aspects of machine learning. Thank you Prof. Ng!

von Swapnil M

Oct 28, 2019

As a student of science I already had some exposure to the mathematical background of the course. But I was curious and wanted to learn about the exact implementation of these ideas in practice. The instructor guided me thoroughly through various important concepts of the subject. I am now able to implement these ideas on my own.

von Manoj

Oct 29, 2019


von Rogerio d S A

Oct 27, 2019

This course is very good introduction to Machine Learning. It goes beyond the basics and it is a real challenge. The tools given like Discussion Forums are of great help! I spent many hours on it and they were worth it! Thank You!

von Masrur M

Oct 29, 2019

Great introductory course.

von Rohan M

Oct 29, 2019

Fabulous course. Learned an enormous amount and would highly recommend this course to anyone interested in understanding machine learning.

von Abdelhady A

Oct 27, 2019

A great intro to machine learning with well structured programming tasks to help you understand the algorithms ecplained

von zhaobo

Oct 27, 2019

it is useful to me , thanks very much!

von Shpati K

Oct 27, 2019

Excellent course!

von Juan J E G

Oct 27, 2019

Excellent course, instructor and materials!

von Shaurya M

Oct 28, 2019

Great ML course for a beginner. From very basic to expert level of learning. You have put effort into this course and it worth it.

von Thiago H S S

Oct 28, 2019

One of the best Machine Learning introductory courses available which will give you the necessary foundation to start your first projects. The classes are very well designed and the progression through the concepts and techniques feels natural. Andrew Ng explains difficult topics in such a understanble way that you will hardly feel lost throughout this course, he is a great teacher. Overall this course helped me to kickstart career into ML and I strongly recommend it for aspiring data scientists and ML engineers.

von Kunal M

Oct 29, 2019

Exceptional effort by the professor to explain the concepts of machine learning. The usage of octave was a challenge - while it simplified lot of computation, but more useful language like python would have made the learning more transferable for long term reference and use. That said, I highly recommend this class. Thanks Professor.

von Arindam D

Oct 29, 2019

Well I have heard about this course a lot. I haven't attended any machine learning course earlier though I have taken a statistics course during my masters. I did find this course pretty helpful for my future career. Thanks to Coursera!

von Gurjeet s

Oct 29, 2019

excellent introductory course

von Eric O

Oct 08, 2019

Great course and review of machine learning algorithms.

von Dennis P

Oct 08, 2019

Buen curso de introducción en este tema.

von Vivek V

Oct 09, 2019


von 徐静

Oct 09, 2019

Thank you so much for Dr. Ng's courses. He is so nice and patient, while telling us much about pratical use of machine learning. Highly recommand!

von Piyush A

Oct 09, 2019

It is a great course with good insights for each supervised and unsupervised learning and how to measure the error and how to tune the algorithms after finding the cause.

It will be great if python can also be included as a part for doing exercises. Overall, I am thankful to Andrew Ng for dedicating his time and sharing his knowledge with us

von Surbhi M

Oct 09, 2019

Very informative and learnt a lot. Andrew Ng is very good and provides good explanation.

von eudora

Oct 10, 2019

Thank you very much, teacher Wu!