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学生对 DeepLearning.AI 提供的 Unsupervised Learning, Recommenders, Reinforcement Learning 的评价和反馈

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5,340 个评分

课程概述

In the third course of the Machine Learning Specialization, you will: • Use unsupervised learning techniques for unsupervised learning: including clustering and anomaly detection. • Build recommender systems with a collaborative filtering approach and a content-based deep learning method. • Build a deep reinforcement learning model. The Machine Learning Specialization is a foundational online program created in collaboration between DeepLearning.AI and Stanford Online. In this beginner-friendly program, you will learn the fundamentals of machine learning and how to use these techniques to build real-world AI applications. This Specialization is taught by Andrew Ng, an AI visionary who has led critical research at Stanford University and groundbreaking work at Google Brain, Baidu, and Landing.AI to advance the AI field. This 3-course Specialization is an updated and expanded version of Andrew’s pioneering Machine Learning course, rated 4.9 out of 5 and taken by over 4.8 million learners since it launched in 2012. It provides a broad introduction to modern machine learning, including supervised learning (multiple linear regression, logistic regression, neural networks, and decision trees), unsupervised learning (clustering, dimensionality reduction, recommender systems), and some of the best practices used in Silicon Valley for artificial intelligence and machine learning innovation (evaluating and tuning models, taking a data-centric approach to improving performance, and more.) By the end of this Specialization, you will have mastered key concepts and gained the practical know-how to quickly and powerfully apply machine learning to challenging real-world problems. If you’re looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

热门审阅

ML

Dec 12, 2022

The whole specialisation is a great quick review of main topics. Proper learning requires deeper knowledge of algebra, calculus and python. But these courses are a fast, essential starting point.

ML

Aug 17, 2022

This course is an excellent course for introductory machine learning. All of the topics are covered in great detail and It is an honor to be taught by Andrew N.G, the Great teacher.

筛选依据：

526 - Unsupervised Learning, Recommenders, Reinforcement Learning 的 550 个评论（共 839 个）

创建者 abdelrahman a

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Sep 6, 2023

Thanks a lot for your efforts

创建者 Huajie C

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Feb 13, 2023

Great course, love Andrew Ng.

创建者 Uday S

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Dec 7, 2025

Exceptional teaching quality

创建者 Saatwik U

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Aug 16, 2025

Nice and good for beginners.

创建者 Yongli L

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Jan 4, 2024

Absolutely love this course.

创建者 Harsh J

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Oct 18, 2023

best ml course in the market

创建者 Tanu J

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Oct 11, 2023

Specific, simple and through

创建者 Ananda B

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Jul 3, 2023

A lot of new topics to cover

创建者 Peter R

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Sep 26, 2022

I learnt so much thank you.

创建者 Shah F M

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Aug 21, 2025

best professor , Andrew sir

创建者 Francesco D

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Aug 18, 2025

Great Learning Experience !

创建者 NarasimhaMurthy V

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Oct 15, 2025

Great course for beginners

创建者 Priyam G

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Aug 11, 2025

Crazyy good learnt so much

创建者 nithya v

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Aug 17, 2024

Excellent course material.

创建者 Dietmar M

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Jul 2, 2024

Exiting course, sparks joy

创建者 AARYAV D (

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Sep 9, 2023

It was a very good course.

创建者 ABHINAV K

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Aug 7, 2023

Best course of this series

创建者 Joy B

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Feb 20, 2023

Excellent and informative.

创建者 liguo z

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Oct 8, 2025

This course is well worth

创建者 Hamid B

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Jul 9, 2025

I just can say Thank you.

创建者 Howard L

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Jan 27, 2025

good series for beginners

创建者 Ernesto J O M

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Jan 8, 2025

Nice content and practice

创建者 Jayesh I

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Aug 12, 2024

Great course for Learning

创建者 Feroz K

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Jul 16, 2024

a very informative course

创建者 Srinivas K B

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Oct 25, 2022

Nicely taught! Thank you