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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
32,070 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:

951 - Supervised Machine Learning: Regression and Classification 的 975 个评论(共 6,053 个)

创建者 HY

Jul 8, 2023

It covers the fundamentals which form the proper foundation for machine learning, suitable for people who want to learn about machine learning implementation as a AI specialist / practitioner.

创建者 Gaurav M

Feb 25, 2023

This is one of the best courses I may have ever done in my life. It teaches the basics and the more advanced concepts in such a way that it literally sticks in my mind! I am now dreaming ML...

创建者 Lindsey A E

Sep 18, 2022

Great course. Focused on understanding the concepts and then applying them piece by piece in code with the optional labs an excellent addition for further understanding and learning the code.

创建者 LETONIO J D S

Nov 10, 2025

A didática é muito boa. Ele sempre deixa claro o que é fundamental e o que é opcional. Aprendi os conceitos do zero e consigo montar do zero meu próprio modelo de regressão linear e logística

创建者 Michael S

Jan 13, 2025

Very useful material (even for those with practical and theoretical experience) and a perfect methodological approach. Without a doubt, this is one of the best online courses I have ever seen

创建者 Sreedhar .

Apr 29, 2024

Great course material with excellent labs and explanations. Easy for anyone with some programming experience. Finally, a course that can make learning and understanding ML easier for everyone

创建者 Aquib V

Mar 1, 2024

Amazing content, perfectly curated topics with hands-on labs, although Assignments and labs could be more challenging based on certain level students who already have programming backgrounds.

创建者 Shivansh S

Aug 27, 2023

This the perfect course for beginners on Machine Learning even for those who have little or no programming experience. Best Course, easy explanation and best labs. Thanks for the the support.

创建者 Duy H N

Jul 17, 2023

This course gives you the basic of supervised learning and the math explanation behind supervised learning model. The math behind is quite complicated but Andrew Ng make it easy for everyone.

创建者 Joe A

Mar 24, 2023

Very good course and walks you through every concept needed for Regression and Classification. Thank you Andrew for providing such a great course and looking forward to meeting you one day !

创建者 Jonathan H

Mar 18, 2023

A very clear and well explained introduction to Machine Learning; Andrew's videos are very easy to follow, and he explains the concepts and the maths very well! I really enjoyed this course.

创建者 Rohit M

Sep 30, 2024

This course is excellent. The explanations of the topics are clear and presented in an easy-to-understand manner. It’s incredibly useful for building a strong foundation in machine learning.

创建者 Manvendra S

Jul 9, 2024

The course is best to start with the fundamentals of Machine learning. The course mainly focuses on the theory part and it is the most missing in any other ML course available in the market.

创建者 Anwar K

Nov 28, 2023

Great introduction to Machine Learning. Realising that my math is rusty and need to perhaps take the deeplearning.ai math courses. Professor Ng makes materials relatively easy to understand.

创建者 Kevin G

Aug 9, 2023

The best course I have taken. it translates a complex subject, into something very simple, and what I like the most about this course is how this thing unfolds step by step, until the result

创建者 saurabh d

Apr 24, 2023

I really liked this course. I had been doing regression for good part of my career, but I had missed the terms / labels and was not able to communicate effectively. This has helped me a lot.

创建者 Maha A B

Feb 11, 2023

i really liked the course, but because i am a beginner i will understand more about machine learning especially cost function logistics. after that, i am going to complete the next 2 courses

创建者 Michael M

Feb 6, 2023

Good intro to the underlying theory of regression/classification. I'd applied these techniques at a high level before, but I'd never learned how they're actually implemented under the hood.

创建者 Anupam D

Aug 3, 2022

I like the way jupyter notebooks are designed. It saves time on testing the code because it displays step by step what is happening and allows me to focus on the code logic implementation.

创建者 Gabriel T

Aug 3, 2022

Amazing course explaining the math behind the most famous algorithm. Good explanation of the gradient descent.

Thank you to Andrew Ng and his team! A bit of math background is needed though

创建者 Daksh S -

Mar 2, 2026

This is an amazing course which is well taught and well depicted in terms of visuals and code...love it 10/10...it shows the amazing effort put into making this well in every part of it...

创建者 Ilyas D J

Sep 30, 2025

I am grateful to have Andrew Ng as an instructor. He truly gave me the foundation and intuition in the Machine Learning space. Thank you so much for being such a gift to the world 🌎 ❤️🔥

创建者 Siddhesh D

Mar 14, 2025

The course starts from basic and gradually take you to another level. Great examples, detailed explanation, Assignments, Pratice with hints and last but not the least great tutor Adrew Ng.

创建者 TC G

Feb 16, 2024

Sufficiently in-depth to grasp the basics and do a bit of coding. Would have preferred more coding practice within the module, but most people will probably find it difficult enough as is.

创建者 Minh Q N

Nov 19, 2023

Love the way the course was organised , passionate teacher , amazing content 10/10 , though the assigment can be implemented in a more efficient way but overall it was too good of a course