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

121,038 notes
29,721 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


Feb 20, 2016

Fantastic intro to the fundamentals of machine learning. If you want to take your understanding of machine learning concepts beyond ", Y), model.predict(X)" then this is the course for you.


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.

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226 - 250 sur 28,832 Examens pour Apprentissage automatique

par Robert H

Dec 04, 2018

Great teacher and approach of learning from really basics to actually working applications! Thanks Andrew!

par Jagadeeswara R R

Dec 05, 2018

it is good for beginners to become an expert in data science. Thanks for the useful sessions,assignments and quizzes

par ali a

Dec 03, 2018

A fantastic introduction to machine learning concepts, algorithms, math foundations, and practical advise on applications. Great instructor, great lectures, and very useful programming assignments.

par 赵煜天

Dec 03, 2018

It is a very useful class. Through there are many difficult technical points, it is still easy to learn because of the patient and detailed teaching style. I believe you will love this course if you are planning to learn something about the machine learning

par CittySteven

Dec 04, 2018

Hello, machine world!

par Gaurav B

Dec 04, 2018

Very good

par Sravanthi

Dec 03, 2018

Excellent Course! Thanks Prof Ng.

par 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.

par 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.

par 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.

par 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.

par 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.

par 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。

par kalyan

Dec 03, 2018

Simply the Best.

Thank you.

par 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.

par Dharma P

Dec 04, 2018

Very good course

par 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!

par Liudmyla R

Dec 05, 2018

Great course, great experience!


Dec 03, 2018

mind blowing

par 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.

par 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.

par Thibault R

Dec 03, 2018

Very good course but maybe a bit too long

par Tim v d W

Dec 03, 2018

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