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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
32,040 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

MA

Jan 27, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.

AP

Sep 3, 2022

A​ perfect course for beginners who are seeking to learn machine learning. I want to thank Mr. Andrew Ng and his team for this wonderful course. Thank you so much for providing this quality course.

筛选依据:

6001 - Supervised Machine Learning: Regression and Classification 的 6025 个评论(共 6,045 个)

创建者 Juergen G

Aug 15, 2023

Very nice and helpful for my next career steps.

创建者 Anish I

Jan 29, 2024

too theoretical, not much hands on learning

创建者 Shoaib K

Sep 7, 2024

Fix your week 2 lab exercise the last one

创建者 Houssam T

Sep 21, 2023

i want to see my name on this certeficate

创建者 Thomas S

Feb 2, 2026

the video wont start after poll

创建者 Natalia S

Feb 25, 2024

no math exercises to practice

创建者 wenyi z

Jun 28, 2025

suggest don't include code

创建者 Hershal C

Jan 23, 2026

not beginners lever

创建者 Spikey

Nov 8, 2022

Oversimplified

创建者 Abhinav S

Dec 2, 2022

not good

创建者 Abdulla A

Oct 9, 2025

Lab

创建者 Patricia R

Oct 20, 2023

Me paso lo mismo con el curso anterior y es que si no realizas los laboratorios aunque hayas aprobado todo y a pesar de que los test te dan como aprobados dicen que no apruebas y que quedas en 0%, es algo como reiterativo con coursera asi que me rindo, no continuo intentando sacarme certificados por acá

创建者 Kamil W

Oct 22, 2024

Awful course. Labs aren't explained clearly at all. You pay £37 per month and you end up with a few slides a few hours of explanation and unclear labs. The final graded assignment was a joke as well, the very first exercise was the hardest of them while the rest was trivial.

创建者 DV B

Jun 20, 2024

Mostly I was inundated with Nagware after ever short video segment, only to discover that Machine Learning learning was not even introduced. Wasted much time on trivialities like linear regression. I never learned anything about Machine Learning, per se.

创建者 Naman G

Dec 6, 2024

please help in coding part , theory won't be helping building real world models, please increase lecture length and do include coding part , please otherwise it is just understanding of theory which is of no use unless implemented by ourselves

创建者 Яна М

Aug 5, 2025

Я специально изучала програмирование перед этим курсом и бызы данных но это мне не помогло. Если у вас нет знаний Python/ Nampy/ разных библиотек програмирования/ создания графиков и хорошей алгебры вы не потяните этот курс.

创建者 MAULIK B 2

Oct 11, 2024

Can't access labs even after getting full access what is the use of financial aid if you can't access all the material! If this is how it is gonna be people will probably just use torrent courses :(

创建者 Muhammad T C

Feb 17, 2024

Although i can see that the next course is included in my learning program but i can not progress in it because the system keeps on asking me to pay for the course.

创建者 A. A ( B

Mar 25, 2025

The week 2 assignment is highly unsatisfactory to me. I'm a novice at Python and am getting no feedback that's useful to resolving the persistent problem.

创建者 andualem c

May 19, 2024

I'm very excited to move to the next level of this field i after i took this foundational courses. It is well organized and very engaging course.

创建者 Rishab P

Jan 5, 2025

Labs are not working well. Correct implementations shows as wrong answers. Even hints and the code supposed to be working is marked as incorrect.

创建者 Elijah G

May 15, 2024

This course is not for beginners. If you are not already familiar with programming and advanced math don't waste your time.

创建者 Hossein T

Oct 14, 2024

Lets be honest this course is basic and depend on your free time you can finish this course in less than a week !

创建者 Samantha C

Jun 27, 2024

They don't provide slides, so there's not way to take notes or go back and reference material.

创建者 Erick O

Feb 13, 2026

in the week 2 lab it keep failing me because it what's me to fix a part that you cannot fix