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

4.9
stars
31,721 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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5226 - 5250 of 5,983 Reviews for Supervised Machine Learning: Regression and Classification

By Renato A V e T

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Feb 18, 2023

Great!

By Albert A

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Jan 10, 2023

Great!

By Maaz M

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Dec 3, 2022

Superb

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Oct 29, 2022

Great

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Oct 17, 2022

Great

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Oct 10, 2022

Best.

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Aug 20, 2022

thanks

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Jul 18, 2022

thanks

By RIDER J R

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Jan 17, 2026

Bueno

By Qiwen G

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Dec 19, 2025

good！

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Jul 8, 2025

Great

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Jun 27, 2025

great

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Jun 11, 2025

great

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great

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Mar 18, 2025

GREAT

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Nov 10, 2024

great

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Oct 28, 2024

great

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Oct 14, 2024

keren

By Ahmed Q

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Sep 5, 2024

Great

By Sina Z J

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Jul 30, 2024

Great