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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
30,729 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

AD

Nov 23, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

JG

Apr 26, 2024

Es un curso diferente a los de regresión y clasificación donde solo se enfocan en aplicar los algoritmos de Scikit-learn. El profesor Andrew le da un enfoque profundo al detrás que hay en cada modelo.

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5626 - 5650 of 5,819 Reviews for Supervised Machine Learning: Regression and Classification

By Kritagyay U

•

Aug 28, 2023

The course structure is awesome .

By Abhishek K

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Aug 11, 2023

Optional part should be explained

By Amirhossein N

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May 26, 2023

thanks to Andrew NG. It was well.

By 20ECE053 M A I

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Sep 24, 2022

Really interesting, Good teacher

By M B K

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Oct 13, 2025

very deeply and nicely explained

By Ishit A

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Aug 21, 2023

great explanation for beginners.

By Mohit Y

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Jun 9, 2023

I expected more rigrous course.

By WONG, L H K

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May 23, 2023

No enough mathematical concepts

By Ameya S

•

Aug 23, 2024

Nicely explained for beginners

By Kartik

•

Sep 27, 2025

Needed more questions in quiz

By SS K

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Jun 20, 2025

i like the way of teaching

By M F R

•

Aug 28, 2022

Very well organized course.

By raj t

•

Oct 6, 2024

very helpful for begginers

By Zeyad M A

•

Jul 23, 2024

Lacks end-to-end projects

By Ritil R

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Jul 6, 2023

teach in a very basic way

By F S

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Jun 30, 2023

need more code assignment

By Manish P

•

Oct 29, 2025

Good indepth into basics

By Safwen S

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Jul 29, 2024

lacks practical examples

By Amgad S a h

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Jul 11, 2023

explain more in the labs

By Bharath K

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Apr 16, 2023

Course content was good

By Umesh P

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Oct 13, 2025

Useful and Informative

By Luca

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Mar 9, 2024

at the start too basic

By Samantha H

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May 2, 2023

good theory grounding