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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: • 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....

Top reviews

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.

DB

May 30, 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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4626 - 4650 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Nimish S

•

Jan 2, 2023

Amazing Course

By Ahmed N

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Dec 29, 2022

very very good

By Adam M

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Dec 11, 2022

Awesome course

By Amirhossein S

•

Nov 29, 2022

Awesome Course

By Ahmed S

•

Nov 17, 2022

very goooooood

By Umit B

•

Nov 8, 2022

great job dude

By 李Yaki

•

Oct 22, 2022

clearly stated

By José B P

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Oct 13, 2022

Just perfect!

By Stefano S

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Sep 29, 2022

Great Andrew!

By Larry_Liu

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Sep 27, 2022

Great Content!

By Shan H

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Sep 21, 2022

Great Course!

By jyoti v

•

Sep 5, 2022

Super Course.

By Matome D m

•

Aug 30, 2022

Awesome course

By Felipe Q

•

Aug 24, 2022

amazing course

By ESPIRITU, J B (

•

Aug 16, 2022

very intuitive

By JYOTI S S

•

Jul 26, 2022

Beginner level

By Jakkala S k

•

Aug 22, 2025

very helpfull

By Fabio M

•

Aug 17, 2025

best training

By Martin T

•

Jun 21, 2025

Very helpful!

By Douglas C

•

May 17, 2025

Great course!

By Wu Y

•

Feb 18, 2025

great course!

By Runshi X

•

Jan 18, 2025

Clear logic!!

By Sathvik S G

•

Jan 9, 2025

Very helpful!

By Vinícius M

•

Jan 2, 2025

Great course!

By Miguel O R

•

Dec 18, 2024

Great course!