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返回到 机器学习

學生對 斯坦福大学 提供的 机器学习 的評價和反饋

4.9
119,262 個評分
29,280 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

MN

Oct 31, 2017

Great overview, enough details to have a good understanding of why the techniques work well. Especially appreciated the practical advice regarding debugging, algorithm evaluation and ceiling analysis.

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:

51 - 机器学习 的 75 個評論(共 28,400 個)

創建者 Nicholas D

May 14, 2019

Truly an exceptional class. Not often will someone with a deep proficiency in a discipline have the time or incentive to share their insights and teach to others; this class is a rare exception, and given the vital importance of machine learning to the future, I have a great appreciation and debt to Andrew Ng.

創建者 Abdul Q

Mar 03, 2018

An amazing skills of teaching and very well structured course for people start to learn to the machine learning. The assignments are very good for understanding the practical side of machine learning.

創建者 anand

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.

創建者 Cesare C

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)

創建者 Miguel Á A S

Jul 24, 2019

This course is one of the most valuable courses I have ever done. Thank you very much to the teacher and to all those who have made it possible! I will recommend it to all those who may be interested.

創建者 Fernando A H G

Jul 21, 2019

Exceptionally complete and outstanding summary of main learning algorithms used currently and globally in software industry. Professor with great charisma as well as patient and clear in his teaching.

創建者 Ganesh K A

May 16, 2019

If it was in python, then it would have got 5 star from me.

創建者 Harshal M

Mar 25, 2019

If this course was in python or R it would have been easier to understand. Octave/MATLAB is not that widely used.

創建者 Rui C

Dec 12, 2015

However good the material and lectures may be, the use of an outdated version of Octave (which is not Mac-friendly and exceedingly brittle, to the extent where the supplied code requires manual patching in Windows and Linux) is a complete turn-off and makes it nearly impossible to complete the assignments on time unless you're prepared to spend at least twice as much time debugging your setup as doing the actual assignments.

I'll come back when this is done with R or Python.

創建者 Emmanuel N

Dec 06, 2018

Amazing course. I had no idea of programming and my maths were more than rusted, but the way the lessons are taught, made the way a whole lot easier. If you're like me (zero programing and maths), it's no easy task to complete the course. But if you put the right amount of effort, patience and dedication, combined with the great videos and reference material, is totally doable.

創建者 Bhanuprasad T

Jan 01, 2019

Loved it. Easy and Excellent Course

創建者 Panu M

Jan 02, 2019

Very eye-opening for a person with a very little knowledge of the aspects and maths behind machine learning. The exercises were somewhat difficult since it's been 15 years since my last maths class and I really haven't been doing it since. So a lot of effort really needed, but once you've done it, it feels great!

創建者 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!

創建者 Raneen H H

Feb 04, 2019

Great course - the assignments were extremely helpful and Professor's Ng's explanations set the fundamentals and cover advanced topics in machine learning.

創建者 Joydeep S

Nov 07, 2018

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

創建者 Luís R

Jan 17, 2019

The course has an adequate degree of dificulty. It is not easy. But, the subject matter demands for that specific degree of detail if we really like to actually do something with machine learning.

創建者 Omri M

Jan 16, 2019

terrific course, good balance of both high and ground level teaching. Good, hands-on experience. I actually appreciate the fact it isn't python or R - this way it's not geared toward a specific crowd

創建者 Miklós L

Jan 15, 2019

Amazing class, great lecturer. A really good introduction and overview of machine learning concepts. It often skips the detailed mathematical background, to make it accessible for a wider audience, but I still found that enough information was given that allowed me to work out these details on my own. A lot of effort was put into creating the programming assignments, they provide a great hands-on experience with machine learning algorithms.

創建者 Eugene M

Jan 04, 2019

Very useful course!

創建者 YuShih C

Jan 04, 2019

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

創建者 THIERRY L

Jan 04, 2019

Excellent

創建者 Praveen K

Jan 18, 2019

This course is very well put together from beginning to the end. The simplicity and approach towards teaching this kind of new and complex subject is amazing. I highly recommend for anyone who would like to get into Machine Learning space.

創建者 Roei B

Jan 18, 2019

10/10. Andrew is an amazing teacher. Thanks!

創建者 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.

創建者 Jawsem A H

Jan 21, 2019

Andrew Ng teaching is great! He breaks complex concepts into easier to consume chunks. He not only explains how to implement specific machine learning algorithms, but how to recognize when there are issues with the models you create and how to address them.