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学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

4.9
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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：

4451 - Supervised Machine Learning: Regression and Classification 的 4475 个评论（共 5,932 个）

创建者 Manas D

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Jul 8, 2024

Crisp and concise

创建者 Safal B

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May 14, 2024

Very great course

创建者 Prayoga R S

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Feb 27, 2024

Excellent course!

创建者 Muhammed S

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Feb 24, 2024

Thank you Andrew.

创建者 Kunal

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Feb 18, 2024

loved the course!

创建者 SastryERP2022 C

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Jan 7, 2024

Excellent Course.

创建者 Sailesh S

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Dec 22, 2023

Fantastic course!

创建者 IDEKEL S

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Nov 21, 2023

Very good course!

创建者 Afzal H

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Nov 5, 2023

Best for starter.

创建者 Sadia A

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Oct 2, 2023

Great experience!

创建者 Morteza H

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Sep 26, 2023

Very informative!

创建者 Eleonora K

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Sep 13, 2023

Very good course!

创建者 Sanjeeda S

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Jul 13, 2023

Amazing lectures.

创建者 amin f

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Jul 9, 2023

awesome course!!!

创建者 Lahiru P

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Jun 21, 2023

great opportunity

创建者 Dev A C

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Jun 1, 2023

Excellent course!

创建者 Dũng N H

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May 14, 2023

Excellent course!

创建者 Brandan H

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Apr 28, 2023

Very good course!

创建者 mah'd a

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Apr 26, 2023

Excellent Course.

创建者 Taufik S N

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Mar 31, 2023

Amazing very good

创建者 Małgorzata G

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Mar 26, 2023

excellent course!

创建者 Carel T

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Mar 21, 2023

Excellent, Thanks

创建者 henry l

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Dec 12, 2022

wonderful course!

创建者 1DS21AI001 A N A

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Nov 17, 2022

Excellent course!

创建者 Sudip S C

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Oct 25, 2022

Excellent course!