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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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32,281 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：

4351 - Supervised Machine Learning: Regression and Classification 的 4375 个评论（共 6,078 个）

创建者 Mazen K

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Aug 26, 2023

Highly Recommend this!

创建者 Bodo C

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Aug 24, 2023

I enjoyed this course.

创建者 임준수

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Aug 16, 2023

What a useful lecture!

创建者 Islam A

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Aug 1, 2023

The course is amazing.

创建者 Deleted A

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Jul 29, 2023

Such a helpful course.

创建者 Nicolas H

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May 26, 2023

Very well made course!

创建者 Raghavendra K

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May 21, 2023

Excellent Explanation.

创建者 M R

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May 17, 2023

It is simply excellent

创建者 陈曦

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Apr 9, 2023

very nice, keep moving

创建者 S S

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Oct 24, 2022

A great start with ML

创建者 Karan D

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Sep 26, 2022

Execptional Teaching!

创建者 Tahir I B

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Aug 19, 2022

Really awesome course.

创建者 Helio A

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Aug 5, 2022

Amazing, state of art

创建者 Dev A

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Apr 12, 2026

Best course till date

创建者 Istiyak I

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Dec 26, 2025

ISTIYAK HOSSAIN ISHAN

创建者 NISARGA K S

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Dec 20, 2025

very amazing sessions

创建者 saad e

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Dec 7, 2025

thank you very much !

创建者 Erfan M

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Oct 14, 2025

The best intro to ML.

创建者 Berkh J

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Oct 10, 2025

Perfect for beginners

创建者 Divine J

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Aug 25, 2025

Incredible! Thank you

创建者 Ali D

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Aug 17, 2025

Andrew Ng is the BEST

创建者 Lakshya G

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Aug 5, 2025

Fantastic Course!!!!!

创建者 Marek P

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May 19, 2025

coherent and engaging

创建者 Zak R

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May 10, 2025

Definitely Recommend!

创建者 Alberto F

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May 8, 2025

Genial, muy didáctico