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返回到 Supervised Machine Learning: Regression and Classification

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

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31,304 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：

5851 - Supervised Machine Learning: Regression and Classification 的 5875 个评论（共 5,934 个）

创建者 Mason N

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Dec 15, 2025

I really want to learn ML but I do not have any money to finish the first module

创建者 Mirza J Z B

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Oct 7, 2025

No explanation video on code. Please add some lectures for explaining the code.

创建者 Arnab B

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Jun 23, 2024

Theory part is good but the practical coding part is not much interactive

创建者 Daniel S

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Apr 12, 2024

A bit long winded for problems that can be solved with 1-2 lines of code

创建者 A A

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Mar 16, 2024

the course lacked the many beginner things and was slow enough for me

创建者 Abdallah A

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Jan 5, 2024

The coding parts are not easy to understand on your own as a beginner

创建者 Hardik D

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Mar 2, 2023

3 and half. I wish the course was designed to get us to code more.

创建者 Yuliya A

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Mar 8, 2024

Instructor is wonderful but course structure can use improvement

创建者 Yesid J

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Jul 14, 2024

Esperaba ver un curso más práctico, pero fue demasiado teórico.

创建者 Divyansh M

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Nov 28, 2024

should focus more on coding and things like one hot encoding

创建者 guy h

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Aug 31, 2025

spoon feed you too much compared to other coursera courses

创建者 Ganesh K

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Jul 25, 2023

Course is good but lab assignments and exercises are less.

创建者 shivam s

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Feb 26, 2023

Should also some small projects for better understanding!

创建者 Anirudh S

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Sep 20, 2025

Asking for upgrading but got it from financial aid still

创建者 feeZ

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Sep 25, 2024

it would be better if there were more coding experiment.

创建者 Mohamed a a

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Jul 23, 2023

good course but i wish it was more project oriented

创建者 G G D

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Jun 14, 2025

Good could have added evaluation metrics

创建者 kunal s

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Jun 12, 2023

please include projects in this course.

创建者 Boris A

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May 26, 2023

A lot of theory and a bit of practice

创建者 Nooreldin N

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Jun 20, 2025

It needs more practical exercises.

创建者 Muhammad U A

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May 21, 2025

kind a slow and not interesting

创建者 Josep B P

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Dec 30, 2023

Step down from the old course.

创建者 NITHISH K

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Jun 29, 2025

the recorded video looks old

创建者 Islam I

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Nov 8, 2024

Concept Only no Beyond that

创建者 Sepehr

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Mar 7, 2024

Easy to follow but useful.