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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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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

ED

Apr 13, 2025

Loved Andrew Ng's videos and the hands on Jupyter notebook labs! My understanding of ML has significantly improved thanks to this course and going on to the next course to complete ML specialization!!

JG

Apr 26, 2024

Es un curso diferente a los de regresión y clasificación donde solo se enfocan en aplicar los algoritmos de Scikit-learn. El profesor Andrew le da un enfoque profundo al detrás que hay en cada modelo.

筛选依据：

5651 - Supervised Machine Learning: Regression and Classification 的 5675 个评论（共 5,932 个）

创建者 Henry C

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Jul 28, 2024

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

创建者 laksh j

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Jun 13, 2024

not many practical questions just implementation of the concepts

创建者 Leonardo K S

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Nov 17, 2023

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

创建者 Ravikumar C

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Dec 17, 2022

Good wa to build intution about how a machine learning algorithm

创建者 pratibimb s

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Dec 7, 2024

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

创建者 KISHAN G

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Oct 15, 2023

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

创建者 Manoj a k

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Mar 13, 2023

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

创建者 Lukman K

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Jan 13, 2023

It gave me the fundamental building blocks of Machine Learning.

创建者 Biswadeep M

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Aug 2, 2024

very good course for developing the basics of machine learning

创建者 Tejas P

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Oct 30, 2023

could include data preprocessing , data cleaning , null values

创建者 Faizan T

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Jun 23, 2022

Vectorized implementation in the assignments would have helped

创建者 Prestigebeetle

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Aug 5, 2023

the course was excellent but it lacked actual implementation.

创建者 Sanjay K

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Jun 23, 2023

This course gives me a lot of idea about ML and other stuffs

创建者 Arwa A

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Mar 30, 2024

great explaining but need to explain coding more than this

创建者 Abhishek_Pandey_IITK

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Aug 30, 2023

A nice and wonderful course.

Bounds you from start till end

创建者 Luca B

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May 14, 2023

Interesting course, not too heavy but direct to the point.

创建者 Hammad U

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Aug 8, 2025

Good community and nice instructor Sir Andrew Thanks Alot

创建者 Shravan D

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Aug 25, 2024

may be a bit more mathematics is required to be explained

创建者 Wassim R

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Apr 18, 2023

I hope to find some obligatory labs (20-30% for example).

创建者 Samer A

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Sep 23, 2025

thanks for the valuable materials and the financial aid.

创建者 Vishesh D

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Aug 21, 2024

Great experience with my very first course on ML and AI!

创建者 Aryan G

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Sep 4, 2022

the optional lab code should be explained in the videos

创建者 Vishal V

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Jul 1, 2022

More graded lab sessions could be included. Good course.

创建者 Omkar D

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Jul 19, 2024

requires more practice lab, content is great thank you

创建者 Moisés M B R R

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Oct 25, 2022

Great for those looking to get into Machine Learning.