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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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31,265 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

FA

May 24, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

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!!

筛选依据：

1776 - Supervised Machine Learning: Regression and Classification 的 1800 个评论（共 5,926 个）

创建者 saransh s

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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

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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

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Jan 3, 2023

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

创建者 Ashutosh S

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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

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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 _

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Dec 6, 2025

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

创建者 Ashutosh .

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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

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Jan 7, 2024

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

创建者 SUHAS Y ( G

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Sep 15, 2023

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

创建者 PCloud

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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

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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

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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

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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

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Oct 11, 2022

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

创建者 Nirmala R

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Aug 17, 2022

Crisp videos and very nice illustrations! Implementing gradient descent really helps understand the algorithm.

创建者 omar a

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Sep 13, 2025

One of the best courses i have seen, andrew was very clear, and provided the theorical foundations very well.

创建者 Sukrat S

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May 11, 2025

Very great course, explained each topic in a simplifies manner along with code implementations. Helped a lot!

创建者 Tamara C

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Nov 9, 2024

Las explicaciones del temario son sublimes, muy cercanas y visuales. La aplicación en Python, muy didáctica.

创建者 Rola I

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Sep 20, 2024

الدورة رائعة جدا و مفيدة ، لقد قمت بتعلم الكثير من الأشياء الجديدة و المفيدة في انشاء مشاريع ML ، شكرا رولا

创建者 Darmen M

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Jul 25, 2024

Very beginner friendly course. Experienced learners may view at 1.25-1.5x video speed. Overall, great course!

创建者 Yu Y

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Feb 10, 2024

A clear a thorough introduction to ML. Accessible to anyone with basics of mathmatics and programming or not!

创建者 Leonid H

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Dec 27, 2023

Excellent course for beginners, but you must have knowledge of engineering mathematics to facilitate learning

创建者 Lucas D

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Oct 14, 2023

Going from very simple ideas to advanced math concepts smoothly, I really enjoyed Andrew' pedagogical skills!

创建者 Nina G

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Aug 31, 2023

Very beginner friendly but with enough detail to keep those with more math and programming experience engaged

创建者 Mashrur K

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Jul 14, 2023

I rated this course a five, but only as a excellent pre-requisites (area) to other, even more advanced topics