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
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.

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

Filter by:

5151 - 5175 of 5,857 Reviews for Supervised Machine Learning: Regression and Classification

By Michael C

•

Dec 19, 2023

Great

By LeHuyPhuong

•

Nov 17, 2023

Coool

By Quoc V N

•

Oct 27, 2023

oke \

By Joel E

•

Oct 16, 2023

bueno

By Muhammad R P S

•

Oct 16, 2023

great

By Alessandro G

•

Oct 5, 2023

magic

By Nguyễn N Q G

•

Sep 20, 2023

good.

By cyberphoenix Y

•

Jul 28, 2023

great

By Chidiebere S M

•

Jul 22, 2023

great

By 슈쿠룰로/학생/융합시스템공학

•

Jul 14, 2023

great

By Urmin H

•

Jul 13, 2023

great

By Seyyed M M

•

Jun 3, 2023

Good!

By Taona M

•

Apr 1, 2023

Great

By richard b

•

Mar 8, 2023

great

By Hezbon K (

•

Dec 1, 2022

great

By Edepalli S R K

•

Nov 19, 2022

goood

By ajinkya b

•

Nov 17, 2022

great

By partheniac

•

Oct 22, 2022

good

By Junping W

•

Oct 8, 2022

good

By Garima S

•

Oct 7, 2022

NICE

By Niraj K

•

Oct 2, 2022

good

By West X

•

Sep 28, 2022

Good

By yazidshuqair

•

Sep 21, 2022

great

By 桂崇徳

•

Aug 22, 2022

great

By Richard G

•

Jul 31, 2022

Great