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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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32,078 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

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.

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.

筛选依据：

4401 - Supervised Machine Learning: Regression and Classification 的 4425 个评论（共 6,053 个）

创建者 Jahid h

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Aug 26, 2024

This is the best One

创建者 Adarsh S

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Aug 18, 2024

Excellent Experience

创建者 Genghis L

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Aug 3, 2024

Clear and Structural

创建者 furqan j

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Jul 29, 2024

what a man Andrew Ng

创建者 mohamed f

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Jul 11, 2024

the best course ever

创建者 Abdullah A

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Jun 29, 2024

Recommended for alll

创建者 Jyhjeng D

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May 10, 2024

Very inspiring class

创建者 Parshva M

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Apr 19, 2024

coding was intensive

创建者 Shubham D G

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Feb 26, 2024

Superb design course

创建者 sulaiman s y m

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Feb 13, 2024

is very great course

创建者 Debasis N

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Jan 28, 2024

Thanks Andrew NG! ❤️

创建者 lion

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Nov 13, 2023

Thank you so much :)

创建者 Omer K

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Oct 7, 2023

Excellent Experience

创建者 A S M S I

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Sep 23, 2023

Andrew Ng is awesome

创建者 abhi c

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Sep 7, 2023

Very well structured

创建者 MUHAMMAD U

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Jul 22, 2023

very nice experience

创建者 Mirza Y s B

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Jun 20, 2023

Pretty wellexplained

创建者 Christoph M

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May 12, 2023

Fantastic instructor

创建者 Umang T

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Apr 25, 2023

Simple yet on point!

创建者 Matthew B

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Feb 14, 2023

I really enjoyed it.

创建者 Heitor A A M

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Feb 4, 2023

The best course ever

创建者 Ifeoluwa F

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Jan 18, 2023

Great Course Overall

创建者 Shuvam M

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Nov 30, 2022

love this course sir

创建者 Alan

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Oct 5, 2022

Very well explained!

创建者 SABHAVATH R

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Sep 16, 2022

i am learn new thing