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

4.9
stars
32,110 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 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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4701 - 4725 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By Eldred L

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Jan 12, 2023

Awesome course!

By SUPATH D

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Jan 10, 2023

Awesome Course!

By Radovan M

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Nov 24, 2022

Just fantastic!

By Iandro R

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Nov 18, 2022

Great and clear

By Joshi L

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Oct 29, 2022

Muy buen curso

By anubhavdipsite

•

Oct 26, 2022

Amazing course

By Muhammad M

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Sep 15, 2022

Fruitful course

By tariq s

•

Sep 11, 2022

perfect course

By Mohamed B

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Sep 7, 2022

very wonderful

By Atharv P

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Sep 5, 2022

awesome course

By Lucky C

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Aug 27, 2022

Andrew Ng 我的男神！

By IFEANYICHUKWU F O

•

Aug 10, 2022

Very intuitive!

By Ramkumar

•

Aug 6, 2022

The best course

By Abhishek M

•

Jul 20, 2022

amazing course!

By Robert K

•

Jul 13, 2022

Very well done.

By Mitchell C

•

Jun 21, 2022

Amazing course!

By Benedict N

•

Feb 2, 2026

Well detailed.

By Mohamed Y

•

Jan 14, 2026

Amazing Course

By Ashutosh P

•

Jan 11, 2026

best ml course

By BOURENNANE M

•

Oct 11, 2025

very intuitive

By Mohammed M M

•

Oct 4, 2025

Amazing course

By Amarjeet K 1

•

Sep 7, 2025

great learning

By JONAS J J C

•

Apr 30, 2025

Muy buen curso

By Louis V

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Apr 27, 2025

Great content.

By AASHYA G

•

Mar 31, 2025

awesome course