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

4.9
étoiles
154,002 évaluations
39,295 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
10 nov. 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
10 juil. 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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201 - 225 sur 10,000 Avis pour Apprentissage automatique

par Akash P

14 sept. 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 Junqi J

8 janv. 2021

An amazing course in 2021, in combination with the python assignments on github. Learn a lot, thank you, Andrew. Programming exercise 4 DOES take a lot of time!

par Abhinav P S

20 mai 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

8 avr. 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

5 juin 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

12 févr. 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

29 juil. 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 Carlos A M A

18 oct. 2020

Excellent course to teach the fundamentals of ML and AI. It is the best course and I recommend making the programming exercises a but longer!

par Sohan j

6 juin 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

22 févr. 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

7 nov. 2018

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

par Daniel

7 déc. 2020

I used the python versions of the programming assignments (in the form of jupyter notebooks). Can't recommend enough.

par Cosmin V N

7 août 2015

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

par Naveen K

9 avr. 2020

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

par Luka B

30 janv. 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

6 juin 2019

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

par Nguyễn H T

5 janv. 2019

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

par Lukas C

31 oct. 2020

VERY GOOD!!!! BEST CLASS TO LEARN Machine Learning as a beginner and easy, pretty concise intuitions.

par Anton S

21 mars 2019

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

par dinh

15 déc. 2018

Great course on Machine Learning. I learned a lot!

Thanks to Professor Andrew NG and all the mentors.

par YuShih C

4 janv. 2019

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

par syh

9 févr. 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

25 juil. 2019

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

par Zihao Z

10 févr. 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 Phani M

25 mai 2020

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