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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
32,127 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

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.

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.

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4351 - 4375 of 6,058 Reviews for Supervised Machine Learning: Regression and Classification

By Istiyak I

•

Dec 26, 2025

ISTIYAK HOSSAIN ISHAN

By NISARGA K S

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Dec 20, 2025

very amazing sessions

By saad e

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Dec 7, 2025

thank you very much !

By Erfan M

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Oct 14, 2025

The best intro to ML.

By Berkh J

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Oct 11, 2025

Perfect for beginners

By Divine J

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Aug 25, 2025

Incredible! Thank you

By Ali D

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Aug 17, 2025

Andrew Ng is the BEST

By Lakshya G

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Aug 5, 2025

Fantastic Course!!!!!

By Marek P

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May 19, 2025

coherent and engaging

By Zak R

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May 11, 2025

Definitely Recommend!

By Alberto F

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May 8, 2025

Genial, muy didáctico

By Lee_Infinitee

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Feb 2, 2025

a solid foundation :)

By Fateme Y

•

Nov 6, 2024

Your review(optional)

By Francisco J M S

•

Oct 15, 2024

Andrew is a genius :D

By Vando G

•

Oct 13, 2024

Amazing learning path

By Harshavardhan D

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Jul 6, 2024

great knowledge *****

By AIMANE C

•

May 5, 2024

Really amazing Course

By Harutaka S

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Apr 15, 2024

Andrew Ng is awesome!

By Parham

•

Feb 16, 2024

excellent , brilliant

By Parag P *

•

Jan 4, 2024

Perfect for beginners

By Saqlain M A S

•

Dec 2, 2023

Very Well explained .

By cliffert t

•

Oct 11, 2023

Amazing math and code

By IamDJ

•

Sep 3, 2023

really helpful course

By Mayank C

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Jul 27, 2023

Very well explained!!

By Ahmed S

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Jul 15, 2023

Very deep yet smooth.