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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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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：

4226 - Supervised Machine Learning: Regression and Classification 的 4250 个评论（共 5,934 个）

创建者 Archit B

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Aug 30, 2023

Very Nicely Explained .

创建者 Harrison P

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Aug 20, 2023

Very interactive course

创建者 Nabin A

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Aug 16, 2023

Best for ML foundations

创建者 Hamza J

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Jul 15, 2023

Easy to follow through.

创建者 mohsin f

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May 31, 2023

very nice good concepts

创建者 Sundaresan S

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May 19, 2023

nice and more intuitive

创建者 Arpit S

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May 10, 2023

very informative course

创建者 Amresh G

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Apr 16, 2023

very good for beginners

创建者 RUIZE X

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Feb 18, 2023

very easy to understand

创建者 Mohamed M

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Feb 3, 2023

the course is so great.

创建者 Tuấn A T

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Jan 30, 2023

Easily understandable !

创建者 Om p

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Jan 1, 2023

nice and knowledgeable.

创建者 Rahul D

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Dec 2, 2022

In one word , Amazing !

创建者 Junaid T

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Oct 23, 2022

Excellent Course !!!!

创建者 Anwesha C

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Oct 6, 2022

Excellent explanation.

创建者 邓明

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Sep 16, 2022

Best ML course so far.

创建者 20131A4441 N Y V N S

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Aug 16, 2022

very good for beginners

创建者 SOURAV D

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Aug 10, 2022

Awesome Course to learn

创建者 Walid s

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Aug 5, 2022

good method in teaching

创建者 Saikrishna M

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Jul 31, 2022

Very nice experience .

创建者 Nadir K

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Dec 7, 2025

Learned a lot! Thanks.

创建者 王牛奶

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May 19, 2025

非常好的老师，讲述的课程具有逻辑性，由浅入深

创建者 Tejaswi D

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May 5, 2025

Amazing course content

创建者 Preshit T

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Mar 7, 2025

Best course out there!

创建者 Punith K K

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Feb 1, 2025

Great learning content