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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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31,304 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

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.

DB

May 30, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

筛选依据：

4026 - Supervised Machine Learning: Regression and Classification 的 4050 个评论（共 5,933 个）

创建者 Zion A

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Jan 25, 2025

Love it, Andrew is the best!

创建者 张涵茗

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Oct 19, 2024

best ML course of the world!

创建者 Babak A

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Oct 10, 2024

Easy, basic, and fundamental

创建者 Amit A

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Sep 12, 2024

Taught in best possible way.

创建者 Deleted A

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Jun 21, 2024

very deep and understandable

创建者 Bison

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Jun 1, 2024

Just thankful for everything

创建者 Muhammad B A

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Mar 27, 2024

A great Course for Beginners

创建者 Andy R

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Mar 26, 2024

Excellent Introduction to ML

创建者 Omkar S

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Mar 17, 2024

very helpful for learning ML

创建者 shivam k

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Mar 10, 2024

very well explained concepts

创建者 AjayMalviya

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Jan 20, 2024

i want to open loked ,my lab

创建者 Mr. M S 4 Y B E E

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Jan 17, 2024

very nice interactive course

创建者 Tharindu L

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Dec 3, 2023

Best course I have ever done

创建者 Yi-Ting C

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Aug 20, 2023

I really enjoyed the course.

创建者 Aatka A

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Jun 4, 2023

Thank Excellent contribution

创建者 Dragos D

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May 11, 2023

Very clear and to the point!

创建者 Zejd I

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Apr 6, 2023

Excellent introduction to ML

创建者 Kumar S

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Mar 29, 2023

Crisp, clear course. Thanks.

创建者 manohar k

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Mar 6, 2023

The best course in the world

创建者 Andres F R G

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Dec 29, 2022

Amazing introductory course!

创建者 Alejandro A

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Nov 8, 2022

Amazing classes and teacher!

创建者 Saravanan P

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Nov 4, 2022

Very Good!!!! Really Nice...

创建者 Mohammad M

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Oct 11, 2022

It was perfect

Thanks Andrew

创建者 Sudipta M

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Oct 9, 2022

Simply Amazing, Amazing !!!!

创建者 Naresh A

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Oct 2, 2022

nice course its very useful