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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
121,268 個評分
29,773 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

HS

Mar 03, 2018

My first and the most beautiful course on Machine learning. To all those thinking of getting in ML, Start you learning with the must-have course. Thanks Andrew Ng and Coursera for this amazing course.

ML

Aug 19, 2017

Very helpful and easy to learn. The quiz and programming assignments are well designed and very useful. Thank Prof. Andrew Ng and coursera and the ones who share their problems and ideas in the forum.

篩選依據:

27876 - 机器学习 的 27900 個評論(共 28,895 個)

創建者 Cosmin D

May 08, 2017

Very simple and mathematically unsophisticated (which could be a good or bad thing depending on your background) but well-organised and a generally worthwhile introduction. I'd recommend watching the videos sped up to 1.5x or 2x if you're comfortable with the mathematics since the pace of the videos is otherwise too slow.

創建者 Mashael A

Sep 18, 2017

the presentation

創建者 Hrishikesh l

Nov 30, 2017

Enjoyed so many pragmatic hours in learning the whats,whys,hows and whens of the machine learning concepts.Thanks a lot for making this class available on the internet!

創建者 Muhammad I

Jun 29, 2017

The videos were short but very informative unlike some other Coursera courses. However, including a programming exercise (even if they are small) in the last two weeks would help the students better understand the topics.

創建者 Jasmeet S

Jan 04, 2017

As a newcomer to the topic, I found the course extremely helpful and insightful. Although, it would be better if the assignment problems and projects are extended (i.e. more assignment problems) and are less spoon fed.

創建者 xuliqian_88

Jan 18, 2017

承上启下,逻辑性 强.其中介绍的,机器学习的经验,很值得参考。

創建者 Ayeswarya. S

Mar 04, 2017

good course

創建者 Alexander Z

Jun 02, 2017

A very interesting course in machine learning taught by a high-level professional. Many things are explained intuitively without getting into a complex math. Very good hands-on exercises and quizzes.

創建者 Chandra R

Feb 08, 2017

Great content, great slides, good examples.

However, even though Dr. Ng takes time to explain the fundamental concepts and length and repeats multiple times, when it comes to complex topics, he glances over them. I ended up referring to external (Dr. Hinton, for instance) for deeper understanding.

創建者 THOMAS S

Mar 25, 2017

Overall, the course is very good.

Positives:

Great introduction to machine learning if you've previously never studied it

Covers core machine learning ideas, algorithms and terminology

Beyond covering the core ideas it teaches you how to do machine learning well - avoid common pitfalls, speed up your algorithms, find the most beneficial problems to tackle

I definitely feel I could take on my own machine learning project from beginning to end, based on what I've learned in this course.

The course is well organised and well paced so it's comfortable to get through without getting lost.

Warnings:

The course was more of a time commitment than I was expecting. Keeping up with the weeks is 5-6 hours per week, which is almost adding another work day.

In the first 3 months that I was registered I completed 5 lessons. I only completed the whole course by doing a binge where I completed 7 weeks in 6 days. From other friends experiences doing a binge was the only way they got through Coursera courses as well.

If you are not familiar with statistics or programming I think you will have to cover a lot of outside material just to read all the mathematical notation and do the basic programming exercises.

Although I manage to pass the exercises every week I'm not sure how much of the material is necessarily well embedded in my brain, rather than I just learned it for 24 hours. I think the additional exercises where Coursera has you right up your own summary of a lesson is an effective aid for retaining the material, but those didn't come up often. I would encourage Coursera to have more of those or make them part of the weekly assignments.

創建者 Nordine A

Dec 14, 2016

Best course about Machine Learning I have seen so far. All the explanations are perfectly clear, it really helps. The only bad part is the audio quality which is unpleasant.

創建者 Roch F

Jan 21, 2017

Great course.

I would have liked to have Octave exercises on week 10 and week 11.

創建者 Meera V M

Apr 02, 2018

I feel that the beginning was quite dynamic and nicely paced. The Octave codes are easy to understand, which helped when I wanted to know what was going on behind the scenes. Towards the end, though, we ended up calculating many cost functions. Maybe it makes sense doing that due to their importance, but it felt a bit repetitive.

創建者 Rishab R

Nov 01, 2017

I very beautifully designed course

Andrew Ng has done a great job at making these videos as easy to understand as possible

Although I feel there is bit of interesting factor lacking from the course which is causing most people to leave the course mid way

創建者 秦超

Feb 24, 2017

nice course!

創建者 Ajay K

Feb 16, 2017

a

創建者 Benjamin S

Jan 12, 2017

Great course! Provides an excellent understanding of the possibilities of machine learning and key details to choose the correct analysis/project design. Only frustrating thing is that programming assignments can be quite frustrating in a way that isn't really furthering your understanding of machine learning. Of course, this is probably mostly due to the nature of programming.

創建者 Vivek P

Aug 23, 2017

Very nice course to kick start with Machine Learning.

創建者 Christine

Feb 28, 2017

great- Sometimes I wondered why the true statistical terms - like factor analysis - were never mentioned

創建者 Jaideep K

Feb 05, 2018

assignments were very easy. make a little tough assignments.

創建者 Usama M

Jan 05, 2017

This course is helpful for the one who are new in this field

創建者 Jennifer V W

Apr 25, 2017

I really enjoyed this course. I believe it gives a great basic understanding of what machine learning is and how you can use it. I feel that the programming assignments could be broken up a little better to assess each section the way the PDF suggests to submit the results. Or at least give an option to bail out of the code if you know you haven't completed the other sections. Overall, I am very satisfied with the information provided and the instructor's teaching style. I look forward to learning more on Coursera.

創建者 Thomas F

Sep 14, 2017

Good course. Sometimes very challenging.

創建者 Erik P

Aug 17, 2017

Great introduction to Machine Learning. Altough it is not intended for people that has strong mathematical or algorithmical background, Andrew NG reaches explain in a very detailed way many concepts of ML.

I suggest this course to people that face ML for the first time, not to people that only want to deepen his knownledge.

創建者 Michael C

Nov 03, 2017

Good overview.