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

4.9
121,521 notes
29,841 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

CS

Jul 16, 2019

The course will give you the incites to understand the data driven mathematical functions to write softwares that can behave or change its behavior, based on stimulus (data).\n\nAndrew Ng is excellent

CC

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)

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251 - 275 sur 28,951 Examens pour Apprentissage automatique

par Keval B

Jan 16, 2019

This course really helps with both, the conceptual and practical enhancement in the knowledge of Machine Learning. I would recommend to do the course if you want to start from the basics and at the end you will be able to develop something of yourself. Thank you Andrew Ng

par ADITI K

Jan 17, 2019

I find it very interesting and useful. Thank you!

par Christian K

Jan 18, 2019

A first class overview of machine learning algorithms and use-cases was provided. Even without having a background in computer science the programming tasks could be solved in an adequate amount of time. In combination with the lectures and the support resources for the exercises one could solve even complex programming tasks. Nevertheless the math behind all the algorithms presented was taught very clearly.

par Hüseyin O Y

Jan 17, 2019

Amazing course. Prof. Andrew Ng is the best in the are of AI. He can teach you what you need to know in machine learning area.

par John D

Jan 17, 2019

Amazing course, very good customer service. Highly reccomend!

par Hanzel G H

Jan 18, 2019

Excellent course, the teacher has very good knowledge of Machine Learning.

par Huang , K

Jan 18, 2019

very useful knowledge.

par Wu M

Jan 17, 2019

Fantastic introductory class to ML concepts. Hope to gain more backgrounds in math to really understand what is going on. And hope to have the opportunity to work on ML projects

par ChenGao

Jan 17, 2019

这门课程真的很棒

感谢吴恩达老师的指导,逻辑清晰,例子生动

受益匪浅

希望自己以后能在AI的路上做出自己的一份努力。

谢谢O(∩_∩)O谢谢

--高趁

par Ujjwal B

Jan 17, 2019

Andrew sir is one of the most influential persons in the field of machine learning and AI

the way he has presented the concepts that are thought to be rigorous and complex is simply lucid and very interesting . The course content is good and gives a hands on experience how machine learning and some of its powerful algorithms work and not to mention the underlying mathematical concepts and application.

par Bharat K

Jan 17, 2019

This is one of the best online courses I took, the content is short, good and still covers much depth.

par Pramit A

Jan 18, 2019

I really like the way how learning made easy.

par 杨卫红

Jan 18, 2019

非常好的机器学习课程

par Shiva N

Jan 17, 2019

Amazing course! Enjoyed taking it and strongly recommend to anyone who is interested in learning more about Machine Learning. Andrew Ng is a superb instructor - explained complex concepts in a simple intuitive manner. Thank you for making this course such a great experience.

par jorge l

Jan 17, 2019

Excellent course. Presentation by Andrew Ng is very, very good. He is really an excellent teacher. The material was, literally, amazing. Particularly the neural networks and SVMs. The gradual introduction of complexity is very well thought out. Practical guidance for successful implementation is very valuable. Lastly the supporting material is great, including lesson slides, lecture notes, and particularly the text and code supporting the exercises.

par Rahat C

Jan 18, 2019

My first ML course and really enjoyed it! The concepts were easy to understand and really appreciated the real world experience Professor shared during the course!

par Eli E

Jan 17, 2019

A very comprehensive course that is an excellent introduction to Machine Learning!

par Nitish B

Jan 17, 2019

It's been a great time to learn Machine Learning through this course. Course contents are very good as well as Prof. Ng.

Just wanna say "Thank you so much" Prof. Ng. :)

par veronica y

Jan 17, 2019

Great class for introduction in machine learning! Very easy to understand and follow through.

par Jesus R G

Jan 18, 2019

Best introduction course to the basis of machine learning, clear explanations with exercises to reinforce the Learning, suitable for any person with basic math.

par Bassel A K

Jan 18, 2019

It was a great class to join, lot of things I have learned.

Thank you very much for the great efforts

par Athitaya P

Jan 16, 2019

Great course! However Octave was a bit confusing to use. Still love it! A great introduction to ML

par Yanlei F

Jan 17, 2019

The course open the door of machine learning to me, making me not afraid of machine learning any more.

par aakashmengji

Jan 17, 2019

Its very usefull and very good course

par Pablo P

Jan 16, 2019

Muy buen curso. Se nota la ganas y el gusto de enseñar del Profesor Andrew, por lo que eso motiva a seguir avanzando en el curso y aprender aún más de lo que se ve aquí. 100% recomendado a cualquiera que le gusten estos tópicos, incluso si no se tiene un conocimiento muy acabado de programación o de matemáticas elementales. Destaco también la labor de los tutores que tienen una gran disposición a ayudar a través del foro. Sin ellos, todo hubiese sido mucho más lento y complicado. Los recursos, así como del foro y los tutoriales son de suma importancia y, a mi juicio, están bien diseñados para que los estudiantes realmente puedan resolver sus dudas.