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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
32,311 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:

1876 - Supervised Machine Learning: Regression and Classification 的 1900 个评论(共 6,083 个)

创建者 Gantumur B

Jul 14, 2025

It was a great intro course to machine learning. Loved the examples, practices, and exercises of the Labs.

创建者 Muhammad A

Feb 4, 2025

Learning experience at Coursera has been an amazing journey with talented mentors, particularly Andrew NG.

创建者 Jonathan D

Sep 13, 2024

Thorough coverage of the topic and very well presented by the engaging and highly knowledgeable Andrew Ng.

创建者 Jose L B F

Feb 8, 2024

I 'm very happy for the opportunity to have learned this course. Thank you very much for all the learning.

创建者 Aman D

Feb 4, 2024

Really helpful for starting machine learning, useful guidance along with practical labs just after theory.

创建者 Andy W

Nov 19, 2023

Great lectures and relevant coding lab assignments. They effectively teach the concepts of supervised ML.

创建者 wilson f s

Oct 14, 2023

Es un curso didáctico, que explica con suficiencia los retos de la regresión y clasificación. Recomendado.

创建者 Anshuman A

Sep 9, 2023

Very nice and useful course. Made learning very easy and I hope to use this course ahead in my future too.

创建者 mohammadreza p

Jul 31, 2023

it was really helpful and taught me ML from scratch.

great thanks to everybody associated with this course

创建者 Anurup G

Jul 21, 2023

It was such a slow gradual way of building up to tough concepts. I never felt the burden but learnt a lot.

创建者 Aman S

Jul 7, 2023

It would be better if we had some python tutorial in starting of course.

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创建者 Sayed G

Jun 24, 2023

Very powerful course to get start in practice with ML..

Learned a lot and have funny time with Dr.Andrew :)

创建者 Rubén G

Mar 17, 2023

Thank you very much to all of you from the bottom of my heart!

This was the best course I ever had, by far.

创建者 Lakshya S

Feb 6, 2023

All the labs make the course very interactive and makes it easier for a student to understand the concepts

创建者 Sachin T

Dec 15, 2022

Amazing Course!! Optional Labs are real learning add-ons, one must complete to get thorough understanding.

创建者 Steven

Aug 16, 2022

Detail and clear. There are lots of tips shared by Andrew Ng, which are quite useful in real applications.

创建者 Manuela F

Aug 4, 2025

cours tres interressant j'ai enormement appris. des tiips de base pour faire dumachine learning excellent

创建者 sarthak s

Jun 7, 2025

It was an amazing course i loved each and every aspect of my learning the lab assignments were fun to do.

创建者 Antonione P

May 13, 2025

The course is very good, it was a great complement to what I learned in the professional Master's degree.

创建者 Emre K

Mar 19, 2025

The course is so well-prepared and extremely taughtful that I can be in a fear in case I miss some parts.

创建者 Ashish D

Mar 7, 2024

Great Course! All optional labs are a must to get a practical knowledge of implementing these algorithms.

创建者 Julia N

Feb 26, 2024

I really liked how the course implemented mathematical, yet easy to understand, background of the models.

创建者 Guilherme A B L

Dec 16, 2023

Andrew NG is just an amazing instructor. The course is very well structured and allow you to really learn

创建者 sameer k

Sep 6, 2023

I learned a lot from this course. There was very handy and interesting plots I played with during course.

创建者 Sayed M

Aug 21, 2023

Very best Andrew ng teaching method is amazing. And also the course is very intresting and very important