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Avis et commentaires pour d'étudiants pour Apprentissage automatique par Université de Stanford

4.9
étoiles
148,209 évaluations
37,728 avis

À propos du cours

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....

Meilleurs avis

AA

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.

SC

Jul 11, 2020

One of the best online courses I have attended in a decade. Thank you to Coursera for making this course available. I cannot express my gratitude enough to professor Andrew Ng for this awesome course!

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176 - 200 sur 10,000 Avis pour Apprentissage automatique

par Rajkumar B

Aug 15, 2018

Much better than the lecture on machine learning than that is offered in my university. only problem is that if you are a fluent user of Matlab, you should skip week 1 and 2

par Tushar T

Aug 07, 2015

Its amazing course, very detailed and good explanation of each algorithm. Mr Andrew NG has good teaching skills, I am glad that I came across this course. Thanks Cousera. :)

par Ramdhani Y A S

Jun 21, 2020

A Great course for beginner in Machine Learning. Hope the exercise can be updated.

It will be good if decision tree, random forest, and bayesian is added to the course.

par Antoine G

Jan 02, 2020

A really good introduction to machine learning with real and practical examples. I can't believe we did so much in such a short time.

Well done professor Andrew Ng !

par Akash P

Sep 14, 2020

I'm glad to be the part of this Machine learning course by Andrew Ng Sir....and i'm also very thankful to coursera for providing me financial aid for this course...

par Abhinav P S

May 20, 2020

An exciting course that is as good for a beginner as anyone. The references provided were really helpful if one wants to pursue more knowledge on that subject.

par Hicham J

Apr 08, 2020

Very challenging and rewarding course. From concepts to hands-on experience, I enjoyed the journey and would highly recommend this course to my colleagues.

par Jorge L R C

Jun 05, 2019

Even being for a "old" course, it has the very best ground of concepts and techniques of Machine Learning. I am very much satisfied and have learned a lot.

par Danny F B L

Feb 12, 2020

This is definitively an excellent course for beginners. I am graceful with Andrew Ng for the dedication he gave for building this course. Congratulations.

par Ajay T

Jul 29, 2019

Excellent course. Discussion forum help from the mentors was super in the first half of the course but towards the end the mentors did not participate

par Sohan j

Jun 06, 2019

It was an amazing experience in learning Machine learning. I learnt a lot from this course. I thank the instructor, Prof. Andrew.

par Anish K A

Feb 22, 2019

Excellent course. I am not an expert in mathematics, but this course gives me a very good understanding of ML and algorithms.

par Joydeep S

Nov 07, 2018

Excellent course. Anyone interested in Machine Learning should definitely take this course. Thanks Andrew for making this.

par Cosmin V N

Aug 07, 2015

Amazing course. Complex topics explained in a way that anyone with a rudimentary understanding of math can follow.

par Naveen K

Apr 09, 2020

One of the best Machine learning course :) Andrew's way of teaching is really a masterpiece :) Thank you Coursera

par Luka B

Jan 30, 2019

Great course, only a bit updated. Would be wonderfu if there was an update (or additional week of two) for 2019!

par Mai S

Jun 06, 2019

Thanks Andrew for this informative course. I am looking forward to taking deep learning specialize as well.

par Nguyễn H T

Jan 06, 2019

This course is absolutely amazing and suitable for ones who want to begin to study about Machine Learning.

par Anton S

Mar 21, 2019

It's a good way to get an understanding of machine learining principles and to improve your English.

par dinh

Dec 15, 2018

Great course on Machine Learning. I learned a lot!

Thanks to Professor Andrew NG and all the mentors.

par YuShih C

Jan 04, 2019

Great introductory course for Machine Learning using MATLAB/Octave. Highly recommended.

par syh

Feb 09, 2020

从机器学习新人、小白,通过这门课程充分理解了机器学习的原理,掌握了一些机器学习的技巧,并能够根据学到的知识,举一反三,应用到更复杂的机器学习算法的理解中。总而言之受益匪浅。

par runner_yang

Jul 25, 2019

Thank you sincerely! I have learned a lot through this course. I love Ng and coursera!

par Zihao Z

Feb 10, 2020

8个exercise出的非常好,程序中给的note和hint有助于理解计算过程、加深记忆。

吴恩达老师英语很有亲和力,对于我这样的英语听力一般的人来说非常友好

par Phanidhar m

May 25, 2020

It would be great if the assignments would be in python rather than octave.