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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：

5601 - Supervised Machine Learning: Regression and Classification 的 5625 个评论（共 5,935 个）

创建者 David I

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Dec 7, 2022

The course is great. I would prefer for there to be more coding involved from the student.

创建者 Alberto C

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Oct 13, 2024

Great course, it would have been even better to have more practical questions to work on.

创建者 Mauro M

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Apr 24, 2024

Very good course. Explanations are clear. Exercises could be a little bit more extensive.

创建者 Anandi S

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Feb 23, 2023

The explanation was pretty clear however, the code should be explained by the instructor.

创建者 Sudarshan D

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Nov 21, 2024

Real life examples and the lab is the major plus of this course.Informative and worth it

创建者 Hudhaifa I I G

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Dec 31, 2022

it was nice course with hands on lab and extensive visualizing for mathematical concepts

创建者 Mitesh B

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Jul 30, 2025

I really like how Andrew the concepts and motivates to learn more about those concepts.

创建者 Yohan D

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Nov 5, 2024

Super bueno, aunque tiene algunos errores en el codigo, de los laboratorios evalutivos.

创建者 Asnan P

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Jul 8, 2024

its very good class, everything is very good by need some practical it may be excellent

创建者 Raayan D

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May 25, 2023

A good introduction. Wish it wasn't so hand-wavy with the math. The labs are very easy.

创建者 Srivaths G

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Oct 5, 2022

Lovely explaination by the proffessor , the flow and chronology was absolutely perfect

创建者 Reza A

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Jul 30, 2022

All the lectures are good. The only thing could be better is the assignments exercises.

创建者 Ehsan H

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Mar 21, 2025

It could be better if we were more engaged in coding and performing tasks on datasets.

创建者 Purva T

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Nov 29, 2023

Andrew Ng has explained every topic in depth and all lectures are easy to understand.

创建者 SREEHARSH N

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Jun 11, 2023

Great course for those who are looking to step into the world of machine learning!!!

创建者 Rameshbabu

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May 8, 2023

Great Training. Suggest to add one additional lectures to brush up the mathematics.

创建者 Shashank A

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Sep 13, 2024

The last portion(logistic regression) looks a bit rushed than the linear regression

创建者 Pelumi A

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Jun 28, 2025

Good course for foundations and theoretical aspects, not much for practical though

创建者 Ikhlaq A

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Feb 4, 2025

very deep and understandable lectures notes and labs, overall course is excellent

创建者 Eman M

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Sep 22, 2023

Your lab session has timed out If you'd like to continue working, reopen the lab.

创建者 Deleted A

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Nov 29, 2022

There is no actual way to learn the basics of Python, you just CTRL+F other labs.

创建者 메타버스크리에이터

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Mar 30, 2023

처음에는 조금 어렵고 뭐가 뭔지 몰랐지만 점점 익숙해지기 시작했습니다.. 앞으로 자주 방문해서 더 AI에 대한 더 많은 정보를 얻도록 하겠습니다

创建者 Daniel N

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Jul 12, 2022

Interesting, and useful, take on how the different topics relate to each other.

创建者 Joshua E

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Jun 12, 2023

The math can be confusing if you want to understand why the code is what it is.

创建者 LALIT K

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Oct 23, 2022

it was nice ,and with full touch of practical knowledge,it was really helpfull