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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
30,880 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

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.

DB

May 31, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

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4876 - 4900 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Claudio M A

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Aug 17, 2023

Excellente

By Bernard A

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Aug 1, 2023

The best !

By Abdul K

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Jul 17, 2023

just great

By Pouria S P

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Jul 16, 2023

perfectily

By Austing D

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Apr 24, 2023

Fantastic!

By Tomas B F A

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Apr 7, 2023

Excellent!

By David D Z

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Mar 19, 2023

Phenomenal

By Md. N S

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Mar 18, 2023

Excellent.

By Qaiser A

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Mar 18, 2023

VERY GREAT

By Hamza A

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Mar 2, 2023

Satisfied!

By Xueqi W

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Jan 3, 2023

Thank you!

By lily h

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Jan 3, 2023

excellent.

By yuzhuobai

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Nov 26, 2022

Thank you!

By Pavan k C N

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Oct 14, 2022

very good

By Shanaaz A

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Oct 1, 2022

Amazing!!

By PEDRO M A D O

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Aug 22, 2022

Fantastic!

By Gonzalo M

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Jul 21, 2022

Very Good

By Rui J ( S / N

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Jul 19, 2022

Very good!

By Mislav P

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Jul 18, 2022

Fantastic!

By Ibrahim H M A

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Jul 15, 2022

great work

By Sagar K

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Jul 15, 2022

Thank You!

By Shivansh M I I

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Oct 30, 2025

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By Ahmed M

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Oct 15, 2025

Excellent

By Gulsum

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Oct 10, 2025

Recommend

By Shivam B

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Oct 4, 2025

very nice