Chevron Left
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

119,018 個評分
29,228 個審閱


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....



Mar 27, 2018

Very well structured and delivered course. Progressive introduction of concepts and intuitive description by Andrew really give a sense of understanding even for the more complex area of the training.


Sep 27, 2018

One of the best course at Coursera, the content are very well versed, assignments and quiz are quite challenging and good, Andrew is one of the best guide we could have in our side.\n\nThanks Coursera


226 - 机器学习 的 250 個評論(共 28,354 個)

創建者 Gaurav B

Dec 04, 2018

Very good

創建者 Sravanthi

Dec 03, 2018

Excellent Course! Thanks Prof Ng.

創建者 Dawid J

Dec 03, 2018

The first week videos are very poor quality and dificult to hear anything - worry not, the next weeks are nicely recorded. The material is explained nicely and with a lot of examples.

創建者 Ionel C

Dec 04, 2018

An amazing course. Many thanks to Prof Ng and to the Mentors, especially Tom for guidance and help completing the exercises.

創建者 Emir E

Dec 04, 2018

First of all thank you to everyone those who contributed. I have been searching for source to start machine learning to dive in data science for a long time.This is the best course i found.In my opinion it is well balanced, not just applying ML by implementing code or just mathematical theory behind the ML.

創建者 Madrigal S H

Dec 04, 2018

I really liked this course, the content is relevant and useful ton understand how machine learning algorithms works. Andrew Ng explains in an easy way the lessons.

創建者 Pascal28968

Dec 05, 2018



Dec 05, 2018

The course approaches in a simple way the main concepts and steps about machine learning. Besides, the course programming tasks are suitable to learn, validate and deploy the most usued machine learning algorithms.

創建者 zhiyunpeng

Dec 03, 2018

Andrew 教授讲解的由浅入深,非常适合我这样的初学者。

創建者 kalyan

Dec 03, 2018

Simply the Best.

Thank you.

創建者 Milton M

Dec 04, 2018

A great introduction to the Machine Learning world for non-specialists. Andrew Ng manages to cover a wide variety of concepts giving the necessary intuitions of the maths behind but without going too much into technical details. I would have perhaps preferred the coding exercises in a more widely spread language like Python, but actually Octave does the job.

創建者 Dharma P

Dec 04, 2018

Very good course

創建者 Hemanth T

Dec 04, 2018

Awesome course!... Very simple and intuitive explanation of complex concepts. The assignments are really helping me in getting a good hands-on flavor of the learnt concepts. Thanks much Andrew!

創建者 Liudmyla R

Dec 05, 2018

Great course, great experience!


Dec 03, 2018

mind blowing

創建者 Misaliet

Dec 03, 2018

I want to give a four-star rating at first because of the programming is based on Matlab. But the content of the course is still best even with Matlab exercise. It is worth five-star rating.


Dec 03, 2018

I did not have any idea of ML before starting this course. I only had a good base on mathematics and I studied Electrical and Computer Engineering in Greece. Following the course was really easy (in a sense that everything was explained perfectly) and I believe that through the programming assignments you get a very good feeling of how ML algorithms work. I haven't followed an ML course in my university so I don't know what else is out there, this course gave me the confidence to move on and further improve my knowledge. It is clearly one of the best organised courses I've seen on Coursera.

創建者 Mahedi H

Dec 03, 2018

I am so grateful to Andrew Ng for this course. This is one of the best course i have seen so far. I also like to thank to mentors, course mates for help through forum. I am looking for accomplish another course at Coursera.

創建者 Thibault R

Dec 03, 2018

Very good course but maybe a bit too long

創建者 Tim v d W

Dec 03, 2018

Great course, cover a lot of the "basics" of ML.

創建者 Renjie T

Dec 03, 2018

Great course!

創建者 Gunish J

Dec 04, 2018


創建者 Adrià A T

Dec 05, 2018

Ideal course to understand some concepts of machine learning, without putting much emphasis on coding but rather explaining very well the mathematics and methods.

創建者 ayush_kumar

Dec 05, 2018

Excellent way of teaching with very informative contents

創建者 gaozhiping

Dec 05, 2018

very good