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

4.9
121,674 個評分
29,878 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

KM

Aug 11, 2017

Very nicely explained the mathematical topics, even for people like me with some phobia regarding large formulas. Useful hands-on experience with MATLAB coding, which I would have had to learn anyway.

RD

Mar 31, 2018

Perhaps the greatest instructor and the greatest course, I enjoyed it so much I had continued to do it in between my exams and looking forward fto start or deeplearning,ai specialization in a few days

篩選依據:

27951 - 机器学习 的 27975 個評論(共 28,992 個)

創建者 Pascal P

Mar 24, 2018

Enjoyed following the course (videos) and reading notes, resources, discussions as well as doing assignments using GNU Octave (visualizing the results). Well organized. A big thanks to the whole team.

創建者 Jari K

Apr 07, 2018

Technical quality of videos are below average, but content is above average—so we average to solid 4/5.

創建者 Roshan P

May 09, 2018

awesome for beginners

創建者 Niklas M

Jun 05, 2018

Loving the Course so far. Great material.

Only comment (why not five starts), would have liked some bigger programming assignments (with helpful notes and code) where you actually get to do a full use case of machine learning:

Find the data (not get it provided but show where it can be found and how to load it)

Create the datasets and then apply machine learning.

A simple step would have been to find a library with handwritten figures and show how to go about importing the data and start from there. It dowsnät ahve to be explained just exist in the code with some comments.

創建者 Brandon L

Dec 16, 2017

I wish there had been more emphasis on what the data being fed to particular algorithms (especially Neural Networks) actually looked like.

創建者 Evan L

Jun 06, 2018

Details are useful and it can help you understand the related topics.

創建者 Nikhil K

Dec 21, 2017

Can't this course be made available in python?

創建者 Adam C

Feb 07, 2018

Great class, just fix week nine's pdf to not give bad advice on the programming exercise

創建者 MANI K K

Feb 05, 2016

very nice

創建者 Roghayeh M

Apr 19, 2018

It is great, I recommend it.

創建者 Gustavo D S R

Jun 04, 2018

En general es el curso más completo, práctico y muy bien explicado que hasta el momento he podido encontrar en la plataforma. Sólo dos puntos para su mejora:

1.- El curso es demasiado extenso por lo que seria conveniente dividirlo en dos partes, las últimas 5 semanas están impartidas de manera bastante básica y rápidas.

2.- En algunos vídeos los subtitulos en español están demasiado desplazados.

創建者 Ernst v d K

Jan 15, 2018

Low-threshold and quite useful course, teaching many ready-to-apply techniques. Focuses on practical aspects rather than theoretical foundations, which will be ok for many students. Personally I would have preferred a little bit more in-depth treatment her

創建者 Michael R

Feb 25, 2018

The time suggested to complete the programming assignments were too ambitious. "Other users finished this week in 2 hours. Does this information help?". NO, not at all!

創建者 Ram v

Mar 03, 2018

A very good course for getting a good introduction and understanding of machine learning concepts ,Andrew's lecture style makes it very easy to understand the material. Great work Coursera team !!!

創建者 ΘΕΟΔΩΡΟΣ Π

Apr 21, 2018

Very Good. Student friendly. Difficult concepts explained with the simpliest way. One video lecture update may be required. Also some weeks overload can be moved to other weeks.

創建者 Sergey P

Feb 02, 2018

Too basic in the beginning. However, I do like the visual examples and if the course will keep chewing in such a details more complex subjects, that would be a great course!

創建者 Tomoki I

Mar 24, 2018

I am a Ph.D. student studying biology at a Japanese university. I decided to enroll this class because recently, many scientists apply machine-learning algorithms to various biological analysis.

Through this class, I learned a lot about machine-learning, and among them, the most worth thing is that what field should I learn more to apply ML. I learned basic knowledge to run ML by myself. This practical knowledge will help me to learn ML more.

There is just one thing to improve this course; Dr. Ng said that there are no problems even if we cannot understand the theories in some algorithms, but it will be helpful to tell us when it gets to be a problem if we cannot understand the basic mathematical theories.

I want to say thank you to Dr. Ng.

創建者 Kshitij L

Mar 12, 2018

nice explanation of every aspect in machine learning with appropriate examples.

創建者 CARLOS G G

Jun 20, 2018

un buen curso

創建者 bhavna c

Jun 26, 2018

its very nice to learn this course .

創建者 Alexey

Mar 01, 2017

Interesting and useful course as for me.

創建者 SHIVAM G

Jul 04, 2018

It can be 5 star If was review by andrew ng which is not the caseweek5 is full of errors.

創建者 Macklin F

Nov 24, 2017

Great course. The programming assignments at times were a little too guided. I would have liked a more open project to work on, but learned a lot.

創建者 Edukondalu V

May 08, 2018

interesting

創建者 Robert P

Apr 17, 2018

The material is somewhat outdated, but it makes a great introduction to Machine Learning and provides context for where the field is now.