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

4.9
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5,489 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

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.

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 .

筛选依据：

551 - Unsupervised Learning, Recommenders, Reinforcement Learning 的 575 个评论（共 864 个）

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

创建者 Gardila A

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Sep 17, 2025

Un excelente aprendizaje

创建者 Anas 2

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Jun 7, 2025

It is an amazing course.

创建者 Maximilian S

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Sep 21, 2024

Very motivating lecturer

创建者 Jonathan P O

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Jun 21, 2024

It´s a completely course

创建者 Nabil G

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Jan 11, 2026

Very Informative Course

创建者 Papa M N

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Mar 6, 2025

Really really intertind

创建者 Julien F

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Jul 12, 2024

Andrew, you're the best

创建者 Cao T M Q

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May 30, 2024

This course is awesome!

创建者 Yixiao D

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Jan 22, 2026

Great course by Andrew

创建者 Ayman M

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Nov 8, 2025

My best statrt poin 🙌

创建者 Arpitha R

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Oct 29, 2025

Very good introduction

创建者 Damilola A

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May 24, 2025

Andrew Ng is the best!

创建者 刘士毅

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Mar 6, 2025

非常棒的课程，帮助我建立机器学习的概念的方法