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Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
30,810 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥� Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥� 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鈥檚 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鈥檙e looking to break into AI or build a career in machine learning, the new Machine Learning Specialization is the best place to start....

Top reviews

MA

Jan 28, 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 糖心vlog官网观看.

AA

Apr 30, 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.

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5601 - 5625 of 5,834 Reviews for Supervised Machine Learning: Regression and Classification

By Konouz A

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Aug 6, 2023

really great, i wish tho there was more on coding

By Devender S

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Jul 30, 2022

A well designed course to learn Machine Learning.

By Ran S

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Jan 4, 2025

Detail and helpful with understanding the theory

By Jerry Y

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Jul 15, 2023

Could have given vide walkthrough for the coding

By Ali F

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Jun 6, 2023

A beginner level course. Great foundation topics

By Tom P

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Aug 24, 2022

Would be nice to have more rigorous mathematics

By Lucky V

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Dec 29, 2024

this course is superb, especially for beginners

By LAVANYA D (

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Feb 5, 2024

Interesting course with interactive assignments

By Chris O

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Oct 7, 2023

Really enlightening and helpful. Very educative

By Samir A

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Aug 12, 2023

Best Machine Learning course for the beginner .

By Riccardo D

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Nov 9, 2022

Graded exercises should in my opinion be harder

By VISHVESH B (

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Sep 23, 2022

More practical knowledge should be focused on.

By Ali R

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Aug 13, 2024

Great course to learn about Machine Learning.

By Dainius K

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Feb 28, 2023

a bit too theoretical but it was interesting.

By Mouad K

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Sep 15, 2024

More frequent labs would have helped me more

By Kashif S

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Sep 20, 2023

The lab exercise should be more interactive.

By Yellampalli S A

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Feb 22, 2024

Should make the Labs a bit more challenging

By arshdeep s s

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Jun 17, 2023

week 3 is tough but this course is amazing

By Saikat K

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May 20, 2023

The material and course structure was good

By Mykola S

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Jun 24, 2022

a bit more complicated tests will be good

By Bhanu P G S

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Dec 31, 2023

Codes re directly coded and not explained

By TICHKULE R R

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May 19, 2025

little too outdated for today's scenario

By Balasubbaiah L

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Nov 9, 2024

required more realtime usecase scenarios

By Sabtain K

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Mar 25, 2024

Wish there were a bit more project work.

By Sandeep T

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Jun 25, 2023

Gradient descent concepts were not clear