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
32,290 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.

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：

5976 - Supervised Machine Learning: Regression and Classification 的 6000 个评论（共 6,080 个）

创建者 Jack B

•

Jul 14, 2023

Much more of the lesson content needs to be focused on the code, rather than the underlying maths, seeing as it is purely code which is assessed.

创建者 Rob I

•

Jun 12, 2023

Love the trainer. Would have been nice to start coding earlier. By the time we were called to actually write code, it was way too late.

创建者 Seyyed F A N

•

Jun 23, 2024

The videos were really helpful, but the optional labs were useless. Besides, the practice labs felt like you are jumping few steps.

创建者 eklektek

•

Jul 20, 2022

Doesn't really enable "DeepUnderstanding" - all abit rushed. Spend time afterwards going through more examples with more rigor.

创建者 K G E

•

Apr 28, 2025

course is well structured, still if u want to learn and practice the labs, u need good python skills, but for knowledge its best

创建者 Tanvi P

•

Sep 29, 2025

I just started today. i wanted to try if i can access other week context. why is it showing week 3? i am confused.

创建者 Rollie O K

•

Sep 20, 2023

Had problems with Python. I does so much for you it sometimes makes it difficult for a C, C++ or Java programer

创建者 Hosein F

•

Oct 20, 2022

Lectures were very clear and smoothly explained but the discussed consepts were only for complete begginers.

创建者 Muhammad B

•

Dec 4, 2023

Thank you sir . I learned many new things from this course which will help me to much in my research work..

创建者 Serkan G

•

Oct 8, 2025

It's a good program, but unfortunately you can't get the certificate while it's in the free trial version.

创建者 Mark S

•

Sep 4, 2024

Good for absolute beginners with no background. Too slow and peace-meal information for anyone else.

创建者 karthik k

•

Oct 11, 2024

The explanation of the theory is good, but there is no explanation at all when it comes to coding

创建者 Herman H

•

Sep 23, 2025

looking for online coarsens for cnc operating my own I am in country 2 hrs from edmonton ab.

创建者 Xander N

•

Oct 18, 2023

Lot of great learning, but not taking into account using a lot of newer open source options.

创建者 SACHIN I

•

May 25, 2024

Everything mostly taught was theory.I learnt very few concepts of coding.Disappointed!!

创建者 Mirza J Z B

•

Oct 7, 2025

No explanation video on code. Please add some lectures for explaining the code.

创建者 Arnab B

•

Jun 23, 2024

Theory part is good but the practical coding part is not much interactive

创建者 Daniel S

•

Apr 12, 2024

A bit long winded for problems that can be solved with 1-2 lines of code

创建者 A A

•

Mar 16, 2024

the course lacked the many beginner things and was slow enough for me

创建者 Abdallah A

•

Jan 5, 2024

The coding parts are not easy to understand on your own as a beginner

创建者 Hardik D

•

Mar 2, 2023

3 and half. I wish the course was designed to get us to code more.

创建者 Yuliya A

•

Mar 8, 2024

Instructor is wonderful but course structure can use improvement

创建者 Yesid J

•

Jul 14, 2024

Esperaba ver un curso más práctico, pero fue demasiado teórico.

创建者 Divyansh M

•

Nov 28, 2024

should focus more on coding and things like one hot encoding

创建者 guy h

•

Aug 31, 2025

spoon feed you too much compared to other coursera courses