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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
30,502 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.

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5501 - Supervised Machine Learning: Regression and Classification 的 5525 个评论(共 5,781 个)

创建者 Tanish J

Aug 17, 2024

A little more of the underlying mathematics would have been appreciated

创建者 michalis l

Dec 13, 2024

Great intro course The code assignments should may be more challenging

创建者 Houimli M M

Feb 26, 2023

I strongly recommend this course as a first step in machine learning .

创建者 عبدالله ج

Sep 19, 2022

near to ferfection but you need to add a week for data preprocessing

创建者 Jay D

Oct 3, 2025

Lots of information but needs more focus on the actual coding aspect

创建者 Abhinandan S

Oct 11, 2024

may be you can try to include some good projects for what you taught

创建者 erick

May 4, 2023

enjoyable , took me 3 months to finish.

I found it very informative

创建者 Hrishikesh K

Nov 9, 2024

It would have been better if the assignment were a bit more tough.

创建者 Rahul C

Aug 13, 2022

Amazing course. Extremely well made and concise. Thank you Andrew.

创建者 Sebastian C S

Oct 9, 2025

me gusta el curso tiene los materiales necesarios para aprender,.

创建者 VISHVAADARSHAN A A

Dec 24, 2023

I encountered significant difficulty while completing the course.

创建者 Prathamesh K

Jul 17, 2023

I think there should be mere coding exercises, theory was perfect

创建者 Md.Emon 2

Jan 1, 2023

Regularization wasn't clear. Other than that the course was great

创建者 Henry C

Jul 28, 2024

Hands on course in machine learning with Practice Lab in Python!

创建者 laksh j

Jun 13, 2024

not many practical questions just implementation of the concepts

创建者 Leonardo K S

Nov 17, 2023

I would like to have more code class not just optional material.

创建者 Ravikumar C

Dec 17, 2022

Good wa to build intution about how a machine learning algorithm

创建者 pratibimb s

Dec 7, 2024

This course should also have more applications of ml in python.

创建者 KISHAN G

Oct 15, 2023

The explanation is very good. Anyone can understand the course.

创建者 Manoj a k

Mar 13, 2023

this course gave me a proper over of how machine learning works

创建者 Lukman K

Jan 13, 2023

It gave me the fundamental building blocks of Machine Learning.

创建者 Biswadeep M

Aug 2, 2024

very good course for developing the basics of machine learning

创建者 Tejas P

Oct 30, 2023

could include data preprocessing , data cleaning , null values

创建者 Faizan T

Jun 23, 2022

Vectorized implementation in the assignments would have helped