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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
31,884 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.

WB

May 23, 2024

amazing course and super easy to follow. my only problem is that it doesn't delve too deeply into the math and science of things and focuses more on practical applications rather than how things work

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3926 - 3950 of 6,020 Reviews for Supervised Machine Learning: Regression and Classification

By Sakib J

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May 4, 2025

Andrew is a good man. Thank you!

By gattu m

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Jan 20, 2025

Very good course and informative

By RAHUL R

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Nov 6, 2024

First step into the ocean of AI.

By Mohamed Y

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Oct 28, 2024

Thank you Andrew and coursera <3

By Utsyo C

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Oct 20, 2024

Amazingly curated and presented!

By James C A

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Oct 1, 2024

Very well taught in all aspects.

By ISHITA M

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Sep 30, 2024

One of the best Coursera course.

By Samrajya B

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Sep 28, 2024

An amazing course for beginners.

By Prathamesh k

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Aug 1, 2024

well explained by the instructor

By Junghoon C

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Jun 12, 2024

I learnt a lot from this course.

By Somnath R

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May 27, 2024

I learned a lot from this course

By Percy A

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May 20, 2024

Very insightful and great course

By Idan D

•

May 7, 2024

Great course, efficient lectures

By JITENDRA K (

•

Mar 20, 2024

good knowladge about this course

By Umer K

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Dec 25, 2023

Best course to satrt learning ML

By Sumaya A

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Dec 15, 2023

Excellent course for ML Beginner

By CHENGHONG L

•

Dec 14, 2023

The best machine learning course

By Kishan T

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Nov 25, 2023

It is the best course! the best!

By Alexander L M

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Oct 27, 2023

Fantastic course and instructor.

By Sara N

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Sep 1, 2023

You are a good teacher Andrew Ng

By MAI A

•

Aug 10, 2023

Wonderful explaining and content

By Prerana b

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Jun 12, 2023

very insightful and interesting.

By Ritik R

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Jun 8, 2023

must do course if beginner in ml

By LALIT C

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Apr 3, 2023

Intuive and Wonderful Experience

By Youcef M

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Mar 11, 2023

It is a very instructive course.