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

4.9
stars
32,070 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

MA

Jan 27, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and Coursera.

AP

Sep 3, 2022

A​ perfect course for beginners who are seeking to learn machine learning. I want to thank Mr. Andrew Ng and his team for this wonderful course. Thank you so much for providing this quality course.

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3701 - 3725 of 6,051 Reviews for Supervised Machine Learning: Regression and Classification

By Viswa R

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Feb 9, 2024

Loved the course very much. Wonderful.

By Asd 4

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Feb 7, 2024

thank you Andrew Ng thank you Stanford

By Abdullah A

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Sep 9, 2023

Perfect for beginners. Great course!!!

By Varshney T

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Aug 26, 2023

best course i have ever studied from .

By Sepehr M

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Aug 16, 2023

Was a good course to start the journey

By Johanna D A

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Aug 4, 2023

excellent course, congratulations !!!!

By Bikesh S

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Aug 4, 2023

great course to start maching learning

By Subham G

•

Jun 9, 2023

Very good course for Machine Learning!

By Neha D

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May 31, 2023

Very Nice course.

Highly understandable

By Yamil A

•

May 18, 2023

very well content along of this course

By Pedro P H

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May 10, 2023

Very clear, step by step explanations.

By Shubham B

•

Feb 6, 2023

This is exactly what I am looking for.

By Abdul Q

•

Jan 30, 2023

Amazing course, Thankful to Andrew N.G

By Lyndon G

•

Jan 12, 2023

Good introduction to ML for beginners!

By Padmaraju R K R

•

Dec 27, 2022

One of the best course for beginners .

By Guotong

•

Nov 12, 2022

great lecture. intuitive and practical

By Navas T

•

Aug 19, 2022

The course is very good for beginners.

By Tebalo K

•

Aug 11, 2022

The best machine learning course ever

By Alaa S A E

•

Jul 14, 2022

good content and excellent instructor

By Karn T

•

Jul 9, 2022

Good Course with Python Implementation

By aadithya m

•

Dec 7, 2025

It was an amazing course by Dr Andrew

By Chamodhya F

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Dec 2, 2025

Very interesting, very useful, Superb

By Pouya B

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Sep 24, 2025

Speechless about this helpful course.

By Juan P M M

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Aug 5, 2025

You understand completely the theory.

By Camila N P C

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Jul 26, 2025

Excelente curso y bien explicado todo