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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
30,925 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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4226 - 4250 of 5,862 Reviews for Supervised Machine Learning: Regression and Classification

By Bodo C

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Aug 24, 2023

I enjoyed this course.

By 임준수

•

Aug 17, 2023

What a useful lecture!

By Islam A

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Aug 1, 2023

The course is amazing.

By Deleted A

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Jul 29, 2023

Such a helpful course.

By Nicolas H

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May 26, 2023

Very well made course!

By Raghavendra K

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May 21, 2023

Excellent Explanation.

By M R

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May 17, 2023

It is simply excellent

By 陈曦

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Apr 9, 2023

very nice, keep moving

By S S

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Oct 24, 2022

A great start with ML

By Karan D

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Sep 26, 2022

Execptional Teaching!

By Tahir I B

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Aug 19, 2022

Really awesome course.

By Helio A

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Aug 5, 2022

Amazing, state of art

By Erfan M

•

Oct 14, 2025

The best intro to ML.

By Berkh J

•

Oct 11, 2025

Perfect for beginners

By Divine J

•

Aug 25, 2025

Incredible! Thank you

By Ali D

•

Aug 17, 2025

Andrew Ng is the BEST

By Lakshya G

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Aug 5, 2025

Fantastic Course!!!!!

By Marek P

•

May 19, 2025

coherent and engaging

By Zak R

•

May 11, 2025

Definitely Recommend!

By Alberto F

•

May 8, 2025

Genial, muy didáctico

By Lee_Infinitee

•

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

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Oct 13, 2024

Amazing learning path

By Harshavardhan D

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Jul 6, 2024

great knowledge *****