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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

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：

5151 - Supervised Machine Learning: Regression and Classification 的 5175 个评论（共 6,053 个）

创建者 Neel P

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Jul 25, 2022

Excellent

创建者 Yona H

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Jul 12, 2022

Excellent

创建者 Thành T

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Oct 1, 2025

exellent

创建者 Sadiq A B

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Jul 8, 2025

love it.

创建者 Ron Y

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Jun 18, 2025

woohoooo

创建者 Vaibhav U

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May 25, 2025

The best

创建者 AMINE A

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Apr 7, 2025

just top

创建者 OliviaChen

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Apr 1, 2025

inspring

创建者 Ankit K

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Mar 12, 2025

its good

创建者 Suhas Y P

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Feb 10, 2025

Good One

创建者 Amjad A G

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Dec 29, 2024

شكرا لكم

创建者 Pawan G

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Dec 8, 2024

Great!!!

创建者 Piyush

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Dec 8, 2024

ml ka 14

创建者 ANIKET B

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Nov 29, 2024

Great !!

创建者 arham j

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Nov 16, 2024

its good

创建者 Nicholas W

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Oct 23, 2024

Amazing.

创建者 Prachet P

•

Sep 21, 2024

Worthy!!

创建者 屈杰敏

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Aug 30, 2024

helpful!

创建者 Yazan H

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Aug 1, 2024

Amazing!

创建者 Kumar D

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Apr 26, 2024

The Best

创建者 Karus H

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Mar 15, 2024

Amazing!

创建者 Imrane G

•

Feb 3, 2024

the best

创建者 鍾易達

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Dec 20, 2023

the best

创建者 Abd a A N

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Nov 8, 2023

not easy

创建者 李嘉洋

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Sep 16, 2023

非常好，浅显易懂