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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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32,078 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：

4051 - Supervised Machine Learning: Regression and Classification 的 4075 个评论（共 6,053 个）

创建者 Dr S R

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Jul 4, 2025

Very useful and easy to learn

创建者 Shubham

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Feb 16, 2025

Enjoyed learning this course.

创建者 Roman S

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Jan 27, 2025

Incredible concise and clear.

创建者 Gojo

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Dec 18, 2024

amazing course, i loved it ..

创建者 Miguel A C Q

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Oct 23, 2024

Solidifique mis conocimientos

创建者 Nitish K

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Oct 15, 2024

Really helpful for beginners.

创建者 tohid b

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Sep 22, 2024

the bad part was it's so easy

创建者 Veysel E

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Sep 8, 2024

Very good introductory course

创建者 Charlie C

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Sep 1, 2024

Clear and easy to understand!

创建者 אסף כ

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Jun 29, 2024

Excellent, interesting, clear

创建者 Haarit C

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Jun 10, 2024

The instructor is amazing !!!

创建者 JEEVAN K

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Mar 4, 2024

clean and well crafted course

创建者 Md T H

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Dec 30, 2023

Excellent Learning experience

创建者 NGOC-DUY D

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Dec 18, 2023

great course, easy understand

创建者 Youwei Z

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Nov 24, 2023

fundamentals are truly great.

创建者 yoss n

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Oct 25, 2023

super amazing! Thanks andrew!

创建者 Cay D

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Sep 8, 2023

Great machine learning course

创建者 C S J

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Jul 5, 2023

andrew neg is a great teacher

创建者 Ayush S

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Jun 14, 2023

Outstanding teaching loved it

创建者 Noman S

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Apr 16, 2023

Very good method of teaching.

创建者 Harsh V T

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Mar 25, 2023

best course I have ever done

创建者 19 徐 徐

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Mar 20, 2023

非常豐富的基礎機械學習內容，就算非本科系的人也很容易理解。

创建者 JANA A A A

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Mar 15, 2023

i really enjoyed learning SML

创建者 Miao H

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Jan 30, 2023

Very interesting and helpful!

创建者 Agustin N

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Jan 28, 2023

Very good! Clear explanations