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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
30,902 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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3776 - 3800 of 5,852 Reviews for Supervised Machine Learning: Regression and Classification

By Pruthviraj C

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Dec 4, 2023

Best! can't expect more than this!

By YALALA V V

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Nov 23, 2023

Excellent course and explanation!!

By Tikhon B

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Nov 13, 2023

Amazing and easy to follow course!

By Janine S

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Oct 26, 2023

Very clear teaching style and pace

By Neeraj K

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Sep 25, 2023

Well taught and structured course.

By Mateusz

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Sep 20, 2023

Really well prepared and executed.

By praveen n

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Aug 29, 2023

Easy explanation of complex topics

By Soumya P

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Jul 18, 2023

Good to have initial understanding

By Aryaman P

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Jul 2, 2023

Mind Blowing experience altogether

By Ramsai k p

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Jun 27, 2023

A really good course for beginners

By Shaktiman C

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May 25, 2023

The videos are easy to understand.

By Mradul B

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May 21, 2023

Great course to start from scratch

By Prabhat R

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Mar 29, 2023

Awesome lecture on regularization.

By Yuxi Z

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Mar 1, 2023

This course really helps me a lot!

By Ezedin M

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Jan 29, 2023

An excellent course for beginners.

By Arijit G

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Nov 28, 2022

the course was absolutely awesome.

By Ali A

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Nov 7, 2022

This was a flawless course for me.

By Ankita R

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Oct 18, 2022

Amazing labs and lab assignments!

By Ivanhoe A

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Oct 12, 2022

Excellent course, very insightful

By Oleksii K

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Aug 31, 2022

The best introductory course ever.

By Rahul k

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Oct 8, 2025

this course is so helpful for me.

By David T

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Jul 4, 2025

A masterclass in Machine Learning

By Sijan T M

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Mar 24, 2025

Its best course i have ever taken

By Shivabhijit S

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Mar 17, 2025

Topics were explained Really well

By Prakash

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Mar 9, 2025

Everything is explained clearly!!