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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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32,084 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

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.

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：

4451 - Supervised Machine Learning: Regression and Classification 的 4475 个评论（共 6,053 个）

创建者 Karen G T

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Aug 26, 2023

Very well explained

创建者 Praneeth N

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Jul 30, 2023

A wonderful course.

创建者 Alaa G

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Jul 7, 2023

It's amazing course

创建者 Twistin T

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Mar 29, 2023

nice course for me

创建者 doru b

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Mar 28, 2023

Excelent Course !!!

创建者 Siavash

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Mar 17, 2023

fascinating course!

创建者 Ilyas R

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Mar 5, 2023

tres bien structure

创建者 gulistan k

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Feb 14, 2023

best thing ever!!!!

创建者 Qianxin W

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Dec 17, 2022

讲解清楚，习题和课程中测试衔接紧密，好

创建者 hoang l

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Oct 17, 2022

so easy for newbie

创建者 Vishnu V

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Sep 26, 2022

really good course

创建者 Josue S M

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Sep 22, 2022

very good! thanks!

创建者 chldntjr

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Sep 3, 2022

good teacher, thx!

创建者 Pranoy D

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Aug 25, 2022

Much details Course

创建者 Jarren J

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Aug 12, 2022

Good for beginners.

创建者 Asim P

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Jul 25, 2022

Thank you very much

创建者 Pak Y H

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Jun 22, 2022

Best online course!

创建者 Gabriel R

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Jun 20, 2022

Very good course :)

创建者 Arhit B

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Feb 19, 2026

Best Course for ML

创建者 Md t S E 2

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Feb 10, 2026

Best Course For Ml

创建者 Bhargavi R

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Dec 13, 2025

Very easy to grasp

创建者 Andrew

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Oct 6, 2025

beiginner friendly

创建者 Johan Z J I

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Sep 27, 2025

really informative

创建者 Vishnu V

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Aug 24, 2025

Outstanding course

创建者 Taher M

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Feb 21, 2025

Best Course for ML