Chevron Left
返回到 Supervised Machine Learning: Regression and Classification

学生对 DeepLearning.AI 提供的 Supervised Machine Learning: Regression and Classification 的评价和反馈

4.9
星
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：

4351 - Supervised Machine Learning: Regression and Classification 的 4375 个评论（共 5,932 个）

创建者 Arkan N

•

Jul 31, 2022

what a great course!

创建者 Jitendra B

•

Dec 3, 2025

such a great course

创建者 Alex E

•

Nov 21, 2025

Clear and enjoyable

创建者 CFCA

•

Sep 17, 2025

Muy bueno: 9 de 10.

创建者 André G

•

Sep 13, 2025

Great introduction!

创建者 Chris K

•

Jul 2, 2025

Very understandable

创建者 Kevin C

•

Apr 17, 2025

phenomenal teaching

创建者 Elvis T

•

Mar 27, 2025

Exceptional lecture

创建者 Odysseas K

•

Mar 11, 2025

Very undrestandable

创建者 Ahmad S

•

Oct 25, 2024

Andrew is wonderful

创建者 Abir E E

•

Sep 15, 2024

A fantastic course!

创建者 ali o

•

Sep 10, 2024

you're the best ang

创建者 Progga P

•

Sep 9, 2024

It was just amazing

创建者 Arijit P

•

Jul 30, 2024

really great course

创建者 Abubakar K

•

Jul 25, 2024

Best for a beginner

创建者 Venkata J B

•

Jul 24, 2024

very helpful course

创建者 Sakthivel S

•

Jul 15, 2024

I love the content!

创建者 yankyx

•

May 25, 2024

easy to understand!

创建者 Soumyadip C

•

Mar 9, 2024

Great for beginners

创建者 Thảo N

•

Feb 4, 2024

it's a great course

创建者 Aashutosh J

•

Dec 2, 2023

Amazing explanation

创建者 samuel 6

•

Nov 13, 2023

Hyper passionnant !

创建者 Mantri J

•

Oct 16, 2023

GOOD PLACE TO START

创建者 wyy

•

Sep 17, 2023

课程难度合理，节奏很舒服，作业也很用心