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学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

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31,343 个评分

课程概述

In the first course of the Machine Learning Specialization, you will: • Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. • Build and train supervised machine learning models for prediction and binary classification tasks, including linear regression and logistic regression 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

MA

Jan 27, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.

AA

Apr 29, 2023

Optional Lab lot more time than mentioned without prior experience of python and libraries used. Its estimated time should be change, it's a lot more than 1 hour. Video and exercises are very good.

筛选依据：

3476 - Supervised Machine Learning: Regression and Classification 的 3500 个评论（共 5,937 个）

创建者 Kimhong H

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Oct 7, 2023

A friendly introduction to machine learning

创建者 VICTOR T M

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Sep 12, 2023

Gran detalle para una primera aproximación.

创建者 Jayraj D

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Aug 3, 2023

Excellent for beginners in the field of ML.

创建者 Amirhossein S

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Jul 24, 2023

It was so useful and great,

Many thanks,

Ames

创建者 Gabriel R

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Jun 5, 2023

Andrew is a great teacher. Well worth it :)

创建者 duchoan m

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May 29, 2023

I really love this course. 5 stars from me!

创建者 Dr. R K G

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May 8, 2023

Loved it. What appeared hard was made easy.

创建者 Polina T

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Mar 28, 2023

Great course! Good structured and detailed!

创建者 Kshitiz S

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Mar 26, 2023

excellent course . From basics to advance .

创建者 Bartosz M

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Mar 11, 2023

I really enjoyed learning from this course.

创建者 ali n

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Mar 2, 2023

goddamn best thank you for financial aid <3

创建者 Yusuf S

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Jan 18, 2023

It was so good to the new learners like me.

创建者 Mohamed I I A

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Oct 17, 2022

Very good introduction course to ML world.

创建者 Mohammed Y

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Sep 24, 2022

As simple as it can possibly be explained.

创建者 Philip G

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Aug 15, 2022

Andrew Ng's course on ML is a masterpiece.

创建者 kareem n

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Aug 9, 2022

Excellent Course, Instructors, and Content.

创建者 plitmuss

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Jul 30, 2022

Very nice introduction in machine learning!

创建者 Basel A

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Jul 27, 2022

Literally the best beginner-friendly course

创建者 Richard G

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Jul 14, 2022

Fantastic introduction to machine learning.

创建者 Yevgen P

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Jul 6, 2022

Very well structured and clearly explained!

创建者 Abdelrhman A

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Jun 22, 2022

World-class and the best course in ML ever!

创建者 Lovish A

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Sep 21, 2025

nice course, with great visualization ^__^

创建者 Nicolae P

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Aug 21, 2025

Concise but comprehensive, practical, fun!

创建者 Cameron B

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Aug 6, 2025

Excellent explanations and easy to follow!

创建者 Ashok S

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May 21, 2025

Very well structured & very good teaching.