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學生對 斯坦福大学 提供的 机器学习 的評價和反饋

4.9
121,373 個評分
29,802 個審閱

課程概述

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....

熱門審閱

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)

NN

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.

篩選依據:

28451 - 机器学习 的 28475 個評論(共 28,932 個)

創建者 VASIM K

Jun 07, 2019

Best Course for Beginner

創建者 Amnon G

Jun 08, 2019

A great introductory to ML. In my job as a program manager it framed my thinking moving forward with our algorithms and how we can spend our time. If you're interested in this topic or want to do this as part of your work, commit and go through it.

創建者 CHAHBAZ A

Jun 09, 2019

Professor Andrew Ng is a great teacher. He delivers the concepts in ways which make them seem very intuitive and sensible. The coursework is good. I only wish that there was more programming involved and maybe an introduction to the programming environments used professionally.

創建者 Robert K

Jun 10, 2019

Fantastic course! I learned a LOT! I think that it would have been great to spend more time on SVMs. I felt that we only skimmed the surface of a rather difficult topic. Also, the course, is several years old now and I am wondering if there are updates that may be needed. Otherwise, I was thrilled to have taken it. Thank-you!

創建者 Sankalp K

Aug 08, 2019

Absolutely awesome course for beginners.

創建者 Santiago H M

Aug 09, 2019

I would apreciate more engaging programming exercises with less helper code and more participation on the students side.

創建者 Anirudh H M

Aug 10, 2019

Well curated course, with an intuitive approach for beginners.

創建者 Yury P

Aug 09, 2019

It's a good course but for me personally, math explanations given weren't deep enough. Though at many times the math part was just right - enough to give intuition but not too overwhelming. But sometimes there was no even intuition insight provided, e.g. why multivariate gaussian distribution can capture data correlations automatically. It is the question if this kind of questions should be a part of the course or not, but for me, they should have been. Another remark is that all test and programming exercises are way too "overguided". I mean for programming exercises solutions are basically written (at least not in Matlab but in English) in files exN.pdf. Questions in quizzes are very much based on precise lecture materials. Numbers may differ but the ideas are exactly the same. I'd prefer that to answer I would have had to do some thinking and generalizing what I'd just heard and not just remembered stuff.

創建者 Ariel S

Aug 12, 2019

It is very good for learning machine learning fundamental. Clear and simple explanations are always better. The audio should be improved for the future courses.

創建者 Satish C P

Aug 13, 2019

Good as an introductory course on AI relevant for a wider audience.

創建者 John M

Aug 14, 2019

Great course. Loved it from beginning to end. Maybe cite sources for the math behind the derivations and proofs throughout this course or at least go into more math.

創建者 Kelvin T D

Aug 12, 2019

This course is a gold mine to machine learning. The instructor is great i also loved the practical programming assignments. I recommend this course to anyone starting out on machine learning.

創建者 SREE K G

Aug 13, 2019

Best prerequisite for beginners.

創建者 Devaraju A

Aug 14, 2019

G

創建者 Subham

Aug 16, 2019

simply amazing! good for solid foundation

創建者 Thanasi M

Aug 15, 2019

Excellent groundwork for understanding the principles of machine learning. Could do with some updates and some more guidance around the programming assessments and more feedback in the quiz assessments.

創建者 Yasir M

Aug 17, 2019

Very good course. However, focusing on math parts more would help get a clear idea about more thins.

創建者 Yuqi Z

Aug 15, 2019

the lecturer skipped too many theories and mathematical derivations. also the programming homework is essentially to just code the cost function and gradients, rather than learning how to structure a ML system.

創建者 Зорин М М

Aug 15, 2019

Sometimes the lack of translation into my native language was critical. In the course I did not have enough practical exercises. But I feel that the course has benefited me, it was very interesting to test myself for my ability to bring difficult tasks to a victorious end. In general, the course was often pleasing, thanks to Professor Andrew Ng for his work!!!

創建者 Lovejeet

Aug 18, 2019

Andrew Sir means Wow, I think he is a man of Achievement

創建者 Dimitri V

Aug 20, 2019

Very cool! Learn a lot, this class demystifies ML and is very practical! Thanks!

創建者 Gursimran S

Aug 18, 2019

good for me

創建者 Rangappa N

Aug 19, 2019

Good Explanation by the professor.He explained everything clearly.

創建者 Mansur A

Aug 19, 2019

This was a superb course. As a student of computer engineering curious about ML, this course definitely helped me plant my foot in that door. Furthermore, this course was taught by an amazing instructor with great communication skills and advice. However, my only gripe with this course is that the latter half of it doesn't come with any reading documents to summarize the concepts learned in the previous video. Other than that, this is a wonderful course for people looking to get into/are curious about ML.

創建者 Tobbe R

Aug 21, 2019

Great content. For me that was a newbie on Octave and had not used Linear Algebra for 20 years it was hard to do the assignments.