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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
31,989 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.

SB

Nov 6, 2022

This course is a brief but thorough introduction. It has a good mixture of theory and practice.Andrew Ng explains every thing very good, understandable and in a fun way.I highly recommend this class!

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5876 - 5900 of 6,034 Reviews for Supervised Machine Learning: Regression and Classification

By Veerendra P

•

Sep 17, 2023

NIce Course

By Kevin S

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Jun 25, 2024

Fast paced

By Salahuddin S

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Jan 25, 2024

it is good

By Haseeb A

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Jul 1, 2025

Fantastic

By 22501A4452 P P R

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Jul 27, 2024

Very good

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Jun 5, 2023

Very good

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Aug 16, 2022

Very Nice

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Aug 12, 2022

Very good

By Ahmed H M

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Aug 10, 2025

great

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Oct 26, 2023

Nice!

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Jan 26, 2026

good

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Apr 5, 2025

Good

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Mar 15, 2025

good

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Jan 30, 2025

Good

By Anshika S

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Nov 19, 2024

nice

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Nov 17, 2024

good

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Nov 9, 2024

Good

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good

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good

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Sep 29, 2024

good

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Jun 20, 2024

good

By Jingyasu k L

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Apr 9, 2024

best

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Dec 20, 2023

good

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Aug 30, 2023

good

By Kshitiz B

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Jul 19, 2023

none