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
32,311 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.

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.

筛选依据：

1801 - Supervised Machine Learning: Regression and Classification 的 1825 个评论（共 6,083 个）

创建者 Jose A R V

•

Jul 1, 2025

I really enjoy it. It is well explained and it has theoretical and practical examples. 100 percent recommended.

创建者 Sumit S

•

Jun 4, 2025

The Course was so good, good for beginners and definitely teaches you something that you will use in your life.

创建者 Vivek A

•

Apr 29, 2025

Excellent course for beginners. Mr. Andrew got excellent knowledge in this area. His teaching style is awesome.

创建者 michael a

•

Sep 13, 2024

perfect course where i understand all the basics and fundamentals of supervised learning great course to enroll

创建者 Helieh H

•

Mar 17, 2024

The course was comprehensive, and its labs were extremely helpful in understanding and practicing the material.

创建者 Johannes B

•

Dec 29, 2023

Introduce vector multiplication in python early in the course. It makes the code that much easier to understand

创建者 Benoît T

•

Jul 6, 2023

Very nice introduction to machine learning, with recommended hands-on labs. Very pleased to have followed this.

创建者 Amirah N

•

Jun 30, 2023

Easy to understand and the lab practices were really helpful to help me visualize the concept learned in codes.

创建者 Deleted A

•

Jun 25, 2023

One of the Best course you can get to get started in the field of Artificial Intelligence and Machine Learning.

创建者 yodha s

•

May 28, 2023

I really loved this introductory course. This course was a great start for me in the field of machine learning.

创建者 Ali M

•

Feb 28, 2023

Thank you so much for interesting and educational courses! I really think that I will enjoy this experience.

创建者 saransh s

•

Feb 6, 2023

Helped me get the basic idea of machine learning and gave me a basic understanding on famously used algorithms.

创建者 wang z

•

Jan 29, 2023

excellent course material!

Feels like being babysit all the way through.

Wishes the course team all the best!!!

创建者 sagar l

•

Jan 3, 2023

truly build your fundamental and strengthen your both theoretical and practical knowledge on machine learning.

创建者 Ashutosh S

•

Nov 9, 2022

I liked the lab part the most. I was able to understand how to implement models using python and its libraries

创建者 Vu T

•

Jul 6, 2022

This course explained so many concepts I found difficult before starting it. 5/5. Thank you very much Coursera!

创建者 Idk _

•

Dec 6, 2025

Great course on understanding the most basic foundation of creating a mathematical model for machine learning.

创建者 Ashutosh S

•

Jun 8, 2025

I like it very much so far because it provides me with a solid understanding of regression and classification.

创建者 Lars F

•

Jan 7, 2024

Great course, fantastic explanation to understand the algorithms and math behind regression and classification

创建者 SUHAS Y ( G

•

Sep 15, 2023

IT WAS A AN INFORMATIVE COURSE UNDERSTANDING THE UNDERLYING THEORETICAL CONCEPTS OF ML WITH PRACTICAL SESSION.

创建者 PCloud

•

Jul 21, 2023

It will be better if the practical labs are more challenging, or make the optional labs as hands on exercises.

创建者 Umjetna I

•

Jun 28, 2023

It was much easier to understand than I thought it would be. I am a total beginner, yet I learned a lot there.

创建者 Xiangnan Z

•

Jun 18, 2023

Andrew's explanation is very intuitive. It is easy to follow and understand the underlying idea of each topic.

创建者 Abhijeet G

•

May 30, 2023

Very much helpful for beginners. Concepts are explained in a very detailed way. Also, all labs are beneficial.

创建者 Liam W

•

Oct 11, 2022

Very helpful for someone wanting to understand the basics of machine learning without going too much in depth