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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：

4776 - Supervised Machine Learning: Regression and Classification 的 4800 个评论（共 5,932 个）

创建者 Lourdu R

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Feb 25, 2025

Just perfect

创建者 Mayur P

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Feb 15, 2025

Very Helpful

创建者 Ndubuisi O

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Feb 6, 2025

Great course

创建者 Monish J

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Jan 30, 2025

Just amazing

创建者 Amritesu p

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Jan 29, 2025

best of best

创建者 박종서

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Jan 14, 2025

best lecture

创建者 Henry M N

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Dec 29, 2024

good content

创建者 Abhishek G

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Dec 22, 2024

Great course

创建者 Bassam S

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Dec 11, 2024

Perfection !

创建者 Ahmed R

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Nov 18, 2024

Just perfect

创建者 Chamindu N

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Nov 16, 2024

Incredible !

创建者 Sbitnev M

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Nov 7, 2024

Best courses

创建者 Aarti S

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Oct 2, 2024

Overall good

创建者 Varsha P

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Sep 12, 2024

Very helpful

创建者 Soumil K

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Sep 1, 2024

great course

创建者 song l

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Aug 25, 2024

great course

创建者 Zeal O

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Aug 21, 2024

great course

创建者 Kareem E Z

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Aug 1, 2024

great course

创建者 Ilya A

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Aug 1, 2024

I love it ^^

创建者 AKSHAT S

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Apr 7, 2024

great course

创建者 Deleted A

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Apr 3, 2024

Great course

创建者 Mridul M

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Feb 29, 2024

great course

创建者 Miguel M P

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Feb 27, 2024

Really good.

创建者 Rakesh R

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Jan 27, 2024

great course

创建者 nikhil y

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Dec 23, 2023

Great course