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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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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：

5076 - Supervised Machine Learning: Regression and Classification 的 5100 个评论（共 5,928 个）

创建者 Kumar D

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Apr 26, 2024

The Best

创建者 Karus H

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Mar 15, 2024

Amazing!

创建者 Imrane G

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Feb 3, 2024

the best

创建者 鍾易達

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Dec 20, 2023

the best

创建者 Abd a A N

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Nov 8, 2023

not easy

创建者 李嘉洋

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Sep 16, 2023

非常好，浅显易懂

创建者 f_mirzaiy

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Jul 11, 2023

fabulous

创建者 Ajaykumar J

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Jun 29, 2023

all good

创建者 Anmol P

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Jun 28, 2023

Awesome!

创建者 Muh. I A

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Jun 9, 2023

Amazing!

创建者 Aladum K

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May 10, 2023

splendid

创建者 Alireza T

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Apr 19, 2023

Awesome!

创建者 廖润龙

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Mar 28, 2023

易懂且讲的很深刻

创建者 JuHo S

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Mar 25, 2023

goood!!!

创建者 Hiếu N

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Feb 14, 2023

worth it

创建者 Oluwasegun E

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Dec 22, 2022

Splendid

创建者 Bill D

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Dec 1, 2022

Amazing!

创建者 Ritwik B

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Nov 16, 2022

Awesome.

创建者 Ebenezer A

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Nov 15, 2022

Perfect!

创建者 Roya A

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Nov 8, 2022

perfect!

创建者 Amir H

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Oct 27, 2022

Amazing

创建者 Josh P

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Oct 1, 2022

Amazing!

创建者 Bardiya R

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Sep 21, 2022

concise

创建者 杨东海

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Sep 18, 2022

Perfect

创建者 Andrew K

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Aug 6, 2022

So good!