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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
30,880 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥� Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥� 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鈥檚 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鈥檙e 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 30, 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 31, 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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4526 - 4550 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Kuchibatla B G

鈥�

Mar 22, 2025

Fun learning AI

By Devang

鈥�

Mar 21, 2025

Assume course !

By Samuel L

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Feb 25, 2025

Exelente course

By Pedro L P

鈥�

Feb 21, 2025

Excelent Course

By Brijesh

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Feb 1, 2025

very impressive

By Morgan Z

鈥�

Jan 30, 2025

Thanks, Andrew!

By RUTWIK N

鈥�

Dec 15, 2024

cool and sooper

By Sofiya R

鈥�

Nov 21, 2024

Amazing Course!

By FRANCISCO J L O

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Nov 13, 2024

Excelente curso

By Venkatesh c

鈥�

Oct 6, 2024

Thanks 糖心vlog官网观看

By Hakim S

鈥�

Aug 27, 2024

thanks coursera

By mahdiyeh g

鈥�

Jul 2, 2024

the best course

By Duncan c

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May 14, 2024

Damn. Crazy Fun

By N G K

鈥�

May 7, 2024

Really well put

By Onkar R K

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May 5, 2024

Amazing course!

By Adham A

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Feb 25, 2024

Very helpful <3

By Aqeel I

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Feb 5, 2024

Amazing Lecture

By Sandeep M

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Dec 31, 2023

Great course!!!

By Satyajeet R

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Dec 13, 2023

just phenomenal

By David R

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Sep 8, 2023

excellent intro

By Victor M

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Aug 3, 2023

Muy emocionante

By ahmed k

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Jul 13, 2023

Amazing course!

By 讗讘讬谞注诐 讘

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Jun 7, 2023

Great course!!

By 膼o脿n K

鈥�

May 28, 2023

greatest course

By Daniel .

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Apr 24, 2023

Amazing course!