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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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5,242 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

AS

Jun 1, 2025

this was a very good course for build a very strong foundation of machine learnignn and many advance this were also taught, with a whole lot of guidence on every step. really appricated thsi course .

AS

Oct 9, 2024

This is a good beginner course . I have been reading around topics and when you jumble around it is hard to follow. This course structure was what i was looking for. i would recommend this to others

筛选依据：

501 - Unsupervised Learning, Recommenders, Reinforcement Learning 的 525 个评论（共 808 个）

创建者 Ankit P

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Aug 28, 2022

This course is just fantastic.

创建者 Sewasew T

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Feb 1, 2025

i just want to say THANK YOU!

创建者 AKULA P R

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Oct 22, 2024

very good learning experience

创建者 Crhis

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Jul 17, 2024

This is just perfect teaching

创建者 Ali A

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Jan 26, 2024

Best course i ever take in ML

创建者 David R

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Oct 7, 2023

Andrew is a wonderful teacher

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 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 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