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Avis et commentaires pour l'étudiant pour Apprentissage automatique par Université de Stanford

4.9
121,521 notes
29,841 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

CS

Jul 16, 2019

The course will give you the incites to understand the data driven mathematical functions to write softwares that can behave or change its behavior, based on stimulus (data).\n\nAndrew Ng is excellent

CC

Jun 20, 2018

good course; just 2 suggestions: improve the skew data part (week 6) and furnish the formula to evaluate the number of iteration in the window from image dimension, window dimension and step (week 11)

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126 - 150 sur 28,948 Examens pour Apprentissage automatique

par BS

Sep 22, 2019

Great comprehensive way to break into machine learning as a subject. I feel confident that this has provided the foundation I need to further explore the subject either by reading up on new topics in the machine learning area or thinking about how to apply machine learning concepts to my personal projects.

par Naveen K

Sep 19, 2019

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

par Vikrant K

Aug 30, 2019

It's so wonderful that it can't be explained by the words and at the same time i am very sad that Ng sir has left us . i just love Ng sir , He is so wonderful person and teacher that can't be explained by the words .It's quite bit a big dream but i am dreaming of some day in the future where i am working with Ng sir on some machine learning problem and he is guiding me as he is doing now . I just love the course and also the mentors Mr. Neil Ostrove and Mr. Tom he had helped us to complete this course and assignment and also solved my useless something baby problems more carefully and i will help other student as guided by Ng sir in completing this course smoothely . and that's all . at the last i want to tell I just fall in love with Ng sir and coursera and the team . i have a big dream of meeting that my favourite Ng sir on some day.

Thank you

par Vincent C

Sep 25, 2019

After finishing the course, I feel much more confident in pursuing more advanced machine learning. The course teaches everything intuitively and in detail but maybe it could use some improvement to achieve perfection. It would be better if the course could provide pointers to some of the topics beyond the scope of the course such as the derivation of the back propagation, svm, pca, etc. Because often times when you search for derivations they might not be very useful for your levels, if course could provide some good references as some lecture notes after the video would be great for the students to gain even more solid groundings of the things behind the hood

Super thanks and thumbs up

par Sunesh P R S

May 17, 2019

This is course just awesome. You get everything you wanted from this course. It covers on all topics in detail, helps in getting confidence in learning all the techiques and ideas in machine learning.

par Bhanuprasad T

Jan 01, 2019

Loved it. Easy and Excellent Course

par Ivan M

Oct 08, 2019

Andrew Ng is such a great person and teacher! This course is just pure gold and this is my first MOOC.

Andrew smoothly guides you through the most important concepts of machine learning, doing so, that you really understand things very well. He eaxplains pretty difficult things in easy way, generalize ideas very well, so, that you don't need to remember lots of things, but actually just understand principles.

Also, with his great experience in the area, he gives you super valuable advice on application of ML and prioritization of work. He knows what are the most important things to know, so you can trust him!

I was happy to learn everything and work on assignments thoroughly, which are of such a great quality!

Tests in each video and at the end of the topic are also great and help to check your understanding!

My life never would be the same :)

Andrew, thank you with all of my heart! Due to your work new generation of AI engineers is appearing!

Now, I will learn Deep Learning Specialization!

par Carlos E R d S

Jul 16, 2019

The course will give you the incites to understand the data driven mathematical functions to write softwares that can behave or change its behavior, based on stimulus (data).

Andrew Ng is excellent

par 王奇

Aug 07, 2015

吴恩达老师的这门课帮助无数学生了解了什么是机器学习,虽然有时候作业会很没有头绪但是通过努力研究一般都能做出来,而且满满的成就感。。感谢andrew

par Luca W

Jan 19, 2017

Thank you Professor Ng for taking the time to produce such a phenomenal course. As mystifying as machine learning can appear to be, your well-paced and digestible teaching style gave me the opportunity to understand. With fantastic lectures, mid-video quizzes, end of topic quizzes, and programming assignments, you as a student are given all the resources you need to absorb the material.

These eleven weeks really gave me the perspective and knowledge I sought for. This is the first online course that I have taken and I am inspired and excited for the future of machine learning and e-learning. The final heartfelt video was a perfect conclusion and I wish to return the sentiment of gratitude and appreciation.

Thank you again, and rest assured that your teaching is having a profound impact on peoples lives across the world.

par Shashank S

Sep 09, 2019

This course was splendidly awesome. I am in my final year from grade C engineering college in New Delhi, India. This course helped me a lot to understand about the basics and gave me deep understanding about the field. Thanks to Andrew NG Sir who made this great website for students like us and such an best class content. Highly Recommended to all!

Thank You!

par John H

Aug 22, 2019

This have been a very good and comprehensive introduction to Machine Learning, IMHO. It have given me the all basic introduction to ML that I could have hoped for. (I'm a senior practitioner of many forms of mathematical modelling and programming, as a former Astrophysics Phd.)

In particular, Andrew Ng is an excellent and experienced lecturer, and it's something that shows in that the course have been tested on thousands of students and over long time, such that for example exercises work very well in every little detail. (Sometimes quizzes may seem a little picky having to get nearly every little question right - but it's for really getting the understanding solid, and you can always improve your grade.)

Therefore, this must be a very good choice as an ML introduction, provided that you're willing to put in the effort of a few weeks on full time. (Albeit 11 weeks is for 'normal' university study schedule, and the course can be completed much faster on full time.) It should also compare well in generality compared to other courses (like Googles Machine Learning Crash Course).

par zhiyiwang

Sep 16, 2019

Very understandable and straightforward class for beginners.

par Sai G K

Jan 19, 2019

This is a great course for someone looking to learn Machine Learning from the ground up. I would suggest this course to everybody from beginners to professionals. Andrew Ng is an awesome teacher.

par Hamed B

Jun 05, 2019

THE BEST COURSE IN ML BY FARRRRRRRR

par Megil P

Mar 16, 2019

Tried different youtube tutorials before, but this course was the one, that gave me true understanding about machine learning and how it basically works. I'll always recommend this course to start a machine learning journey! Thanks to Andrew NG for this course and for his effort!

par Subham

Mar 03, 2019

The real way to learn Machine Learning is this, no black box;understanding using pure mathematics makes it more interesting, and as I was solving the programming exercises I got to know, how simply vectors and calculus can be used to represent complex mathematical formulas. All the hours completing this course was worth. Once I started using machine learning libraries, all concepts were no longer black box for me, suddenly everything started making sense. Highly Recommended course for beginners.

par Gil B

Jun 06, 2019

The instructor gives simple explanations, yet covers all the topics deeply. The coding exercises are well designed and teach you haw to write machine learning with no past experience.

par John M

Dec 13, 2018

Very detailed. The programming exercises were very well made, it was great to be able to implement the parts of the exercise one by one, and see the effect that each step has.

par Tu N

Nov 03, 2019

This is one of the best online course I have learned over many years. Thank you very much Prof. Andrew Ng. Highly recommended for whom want to learn about AI & Machine Learning subject.

par Vivek R

Mar 12, 2019

This course is very well designed, covers a lot of topics with a lot of rigourous detail, but Andrew Ng introduces them giving some intuition about them, before diving into the deeper Maths. Assignments are very challenging, but with some boilerplate code already done, they are immensely satisfying, as you end up achieving with some implementations of pretty cool problems. I have done linear algebra and regression and PCA before, so was able to complete it rather quickly, but this should be very approachable and useful for everyone.

par Mai S

Jun 06, 2019

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

par Jiyuan Z

Mar 03, 2019

Great!

par Lichen N

Aug 28, 2019

深入浅出

par YuShih C

Jan 04, 2019

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