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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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30,502 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：

5601 - Supervised Machine Learning: Regression and Classification 的 5625 个评论（共 5,782 个）

创建者 Ameya S

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Aug 23, 2024

Nicely explained for beginners

创建者 Kartik

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Sep 27, 2025

Needed more questions in quiz

创建者 SS K

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Jun 20, 2025

i like the way of teaching

创建者 M F R

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Aug 28, 2022

Very well organized course.

创建者 raj t

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Oct 6, 2024

very helpful for begginers

创建者 Zeyad M A

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Jul 23, 2024

Lacks end-to-end projects

创建者 Ritil R

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Jul 6, 2023

teach in a very basic way

创建者 F S

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Jun 30, 2023

need more code assignment

创建者 Safwen S

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Jul 29, 2024

lacks practical examples

创建者 Amgad S a h

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Jul 11, 2023

explain more in the labs

创建者 Bharath K

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Apr 16, 2023

Course content was good

创建者 Luca

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Mar 9, 2024

at the start too basic

创建者 Samantha H

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May 2, 2023

good theory grounding

创建者 Phúc T T

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Aug 23, 2025

Thanh you, Andrew Ng

创建者 El S

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Feb 12, 2024

Very well explained!

创建者 Foula L

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Aug 20, 2022

Cours très structuré

创建者 Reinhard M

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Feb 13, 2024

very easy to follow

创建者 NANDYALA V R

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Dec 25, 2022

Great for beginners

创建者 Connect B

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Nov 26, 2022

Easy to understand.

创建者 Patrick G

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Mar 16, 2025

Great presentation

创建者 Ghulam A

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Nov 3, 2024

AMAZING EXPERIENCE

创建者 JISAN A

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Sep 28, 2023

Good for beginners

创建者 Fawad A

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Aug 5, 2023

This is best curse

创建者 SYAMRAJ M

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Sep 21, 2024

good explanantion

创建者 Josef K

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May 15, 2025

perfect training