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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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31,800 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：

5826 - Supervised Machine Learning: Regression and Classification 的 5850 个评论（共 6,004 个）

创建者 El S

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Feb 12, 2024

Very well explained!

创建者 Foula L

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Aug 20, 2022

Cours très structuré

创建者 Armin S

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Dec 4, 2025

It was a good start

创建者 Reinhard M

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Feb 13, 2024

very easy to follow

创建者 NANDYALA V R

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Dec 25, 2022

Great for beginners

创建者 Connect B

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Nov 26, 2022

Easy to understand.

创建者 Patrick G

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Mar 16, 2025

Great presentation

创建者 Ghulam A

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Nov 3, 2024

AMAZING EXPERIENCE

创建者 JISAN A

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Sep 28, 2023

Good for beginners

创建者 Fawad A

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Aug 5, 2023

This is best curse

创建者 SYAMRAJ M

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Sep 21, 2024

good explanantion

创建者 Josef K

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May 15, 2025

perfect training

创建者 Deepak R

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Jul 11, 2022

very nice course

创建者 Silvia G

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Jan 13, 2026

silvia gagliano

创建者 Thiện N

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Sep 16, 2022

Good knowledge

创建者 Madhul K

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Aug 8, 2022

Great learning

创建者 Somtirtha D

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Jan 9, 2024

Great course.

创建者 Juan E

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Jul 29, 2023

g,mbvscMbn<MA

创建者 Rahul C

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Nov 3, 2025

Great Course

创建者 Madan

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Aug 13, 2023

Great course

创建者 Echekwu E

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Aug 6, 2022

Fundalmental

创建者 Vishal B

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Nov 10, 2023

nice course

创建者 Veerendra P

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Sep 16, 2023

NIce Course

创建者 Kevin S

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Jun 25, 2024

Fast paced

创建者 Salahuddin S

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Jan 25, 2024

it is good