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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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32,279 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：

4826 - Supervised Machine Learning: Regression and Classification 的 4850 个评论（共 6,077 个）

创建者 Prof H F

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May 8, 2024

Really good !

创建者 Ankit

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May 1, 2024

great course!

创建者 Liliia E

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Apr 4, 2024

Thanks a lot!

创建者 Alexander J

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Mar 18, 2024

Great course!

创建者 Shivam A

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Mar 14, 2024

Great Course!

创建者 Vidyut K

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Jan 31, 2024

Nicely taught

创建者 Dimitrios - M A

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Jan 28, 2024

Great course!

创建者 nguyen t t

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Jan 6, 2024

nice and good

创建者 Sabeur M

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Dec 20, 2023

Great courses

创建者 Mehdi K

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Nov 10, 2023

perfecttttttt

创建者 Imam U

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Oct 21, 2023

Great for all

创建者 Aditya T

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Oct 6, 2023

v good course

创建者 Liam B

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Aug 29, 2023

Great Course!

创建者 Yoann S

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Aug 11, 2023

Great course!

创建者 Ashwin R

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Jul 18, 2023

Great course!

创建者 Anush R

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Jul 17, 2023

Superb course

创建者 Steve T

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Jun 12, 2023

Great course!

创建者 John J

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Jun 11, 2023

Great course!

创建者 Joyce W

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Jun 9, 2023

best lecturer

创建者 Prem P

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Apr 29, 2023

exceptional!!

创建者 AYYOUB M

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Apr 23, 2023

Great course.

创建者 Emanuele S

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Apr 14, 2023

Just amezing!

创建者 kronux u

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Apr 14, 2023

Great Course.

创建者 Santiago G

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Apr 9, 2023

Great course!

创建者 Karan S

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Apr 7, 2023

Great Course!