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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：

4751 - Supervised Machine Learning: Regression and Classification 的 4775 个评论（共 5,933 个）

创建者 Jiang L

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Jan 16, 2023

Great course!

创建者 Simao E

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Jan 11, 2023

Excellent !!!

创建者 Jasurbek G

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Jan 10, 2023

Great course.

创建者 Lưu G N

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Nov 7, 2022

Great course!

创建者 Tanmay R S

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Oct 10, 2022

great course

创建者 Bartlomiej K

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Oct 4, 2022

Just amazing

创建者 Osama M

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Sep 29, 2022

Thanks a lot

创建者 kalu s e

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Sep 21, 2022

Just perfect

创建者 Jadhav D

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Sep 14, 2022

GREAT SKILLS

创建者 Babak A

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Aug 24, 2022

Great course!

创建者 Jndd15

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Aug 24, 2022

Supa awesome!

创建者 Gabriele M

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Aug 19, 2022

great course

创建者 Erkang X

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Aug 18, 2022

great course!

创建者 Yuwei S

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Jul 29, 2022

Good Lecturer

创建者 Michel M F

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Jun 28, 2022

Great course!

创建者 Trang Q K

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Jun 27, 2022

Great course.

创建者 Cəlal İ

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Dec 11, 2025

great course

创建者 Thumati S

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Nov 16, 2025

Great course

创建者 Nasir A

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Jul 23, 2025

great course

创建者 Shashwata R

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Jul 13, 2025

Great Course

创建者 Premkumar S

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Jun 29, 2025

very helpful

创建者 Sarah Y

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Mar 25, 2025

it was great

创建者 Sadananda B

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Mar 17, 2025

VERY USEFULL

创建者 Lakshay D

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Mar 11, 2025

Very helpful

创建者 FS20EC016

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Mar 10, 2025

great course