Chevron Left
Back to Supervised Machine Learning: Regression and Classification

Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
27,808 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

ED

Apr 13, 2025

Loved Andrew Ng's videos and the hands on Jupyter notebook labs! My understanding of ML has significantly improved thanks to this course and going on to the next course to complete ML specialization!!

FA

May 24, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

Filter by:

4776 - 4800 of 5,327 Reviews for Supervised Machine Learning: Regression and Classification

By Aditi S

•

May 2, 2024

Good

By Muhammad I F A

•

Apr 16, 2024

good

By milan 0

•

Apr 16, 2024

Best

By Meilia I A S

•

Apr 14, 2024

NICE

By Anggi P S

•

Apr 5, 2024

good

By hieu n v

•

Mar 24, 2024

good

By NKG H

•

Mar 17, 2024

good

By slibtec s

•

Mar 11, 2024

good

By Maksim K

•

Mar 10, 2024

good

By Surya P

•

Jan 8, 2024

Nice

By zway w

•

Dec 22, 2023

nice

By ADITYA G

•

Dec 18, 2023

Good

By Rajan L

•

Nov 24, 2023

Nice

By Md. S A

•

Nov 23, 2023

best

By Dini P U

•

Oct 13, 2023

good

By Han Y T

•

Oct 2, 2023

謝謝老師

By Phước T L

•

Sep 24, 2023

nice

By syrine b

•

Aug 13, 2023

love

By Ali G

•

Jul 11, 2023

nice

By Hồ N T

•

Jul 5, 2023

Very

By 조현묵

•

Jun 4, 2023

good

By Ario P

•

May 28, 2023

Good

By Sanjay r

•

May 19, 2023

good

By Data I M

•

May 15, 2023

good

By TA V B

•

Apr 28, 2023

Good