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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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5,496 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

HZ

Jul 21, 2024

Got insights to what Recommender systems are and how it recommends user based on their usage and got to know how Reinforcement learning works and Successfully landed the lunar lander.

HA

Sep 25, 2022

T​he content was details, explained thoroughly and understandable. But, when it came to implementation, few more labs similar to the structure of previous course could have improved it more.

筛选依据：

726 - Unsupervised Learning, Recommenders, Reinforcement Learning 的 750 个评论（共 864 个）

创建者 Achyuth S

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Aug 2, 2023

Awesome.

创建者 Navin D

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Oct 21, 2022

perfect

创建者 Gelli V S G

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Oct 9, 2022

Awesome

创建者 하재현

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Sep 3, 2022

perfect

创建者 Ramkumar

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Aug 19, 2022

the best

创建者 anwar k

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Feb 1, 2026

amazing

创建者 shijie j

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Jul 12, 2025

非常棒的课程！

创建者 mfl828

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Apr 13, 2025

awesome

创建者 Khaled Z

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Apr 5, 2025

perfect

创建者 YACINE

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Jan 21, 2025

love it

创建者 Yanuar Z

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Dec 29, 2024

Awesome

创建者 Onur C C

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Oct 25, 2024

amazıng

创建者 Deni K

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Oct 11, 2024

amazing

创建者 Ifeanyi A

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Aug 31, 2024

Amazing

创建者 Hesam A

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Jul 8, 2024

perfect

创建者 Fausto R

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Jun 22, 2024

Ta weno

创建者 Muhammad K I

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Apr 15, 2024

awesome

创建者 Saffanah N F

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Apr 13, 2024

amazing

创建者 Idir b

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Feb 28, 2024

Awesome

创建者 Sakshi P

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Jan 15, 2024

awesome

创建者 Moaaz m

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Mar 23, 2025

Thanks

创建者 Ferry A

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Oct 23, 2024

greatt

创建者 Huỳnh T T

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Jul 26, 2023

Great!

创建者 刘楚墙

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Mar 31, 2023

useful

创建者 seyed m s m

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Dec 15, 2022

THANKS