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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
32,127 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

DB

May 30, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

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.

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4826 - 4850 of 6,058 Reviews for Supervised Machine Learning: Regression and Classification

By Steve T

•

Jun 12, 2023

Great course!

By John J

•

Jun 11, 2023

Great course!

By Joyce W

•

Jun 9, 2023

best lecturer

By Prem P

•

Apr 29, 2023

exceptional!!

By AYYOUB M

•

Apr 23, 2023

Great course.

By Emanuele S

•

Apr 14, 2023

Just amezing!

By kronux u

•

Apr 14, 2023

Great Course.

By Santiago G

•

Apr 9, 2023

Great course!

By Karan S

•

Apr 7, 2023

Great Course!

By Atif D

•

Mar 23, 2023

all time good

By Sam T

•

Feb 25, 2023

Easy and Fun!

By ChunYa S

•

Feb 22, 2023

Very helpful!

By salim b o

•

Feb 5, 2023

great content

By Abhishek

•

Jan 31, 2023

Just amazing!

By Jiang L

•

Jan 16, 2023

Great course!

By Simao E

•

Jan 11, 2023

Excellent !!!

By Jasurbek G

•

Jan 10, 2023

Great course.

By Lưu G N

•

Nov 7, 2022

Great course!

By Tanmay R S

•

Oct 10, 2022

great course

By Bartlomiej K

•

Oct 4, 2022

Just amazing

By Osama M

•

Sep 29, 2022

Thanks a lot

By kalu s e

•

Sep 21, 2022

Just perfect

By Jadhav D

•

Sep 14, 2022

GREAT SKILLS

By Babak A

•

Aug 24, 2022

Great course!

By Jndd15

•

Aug 24, 2022

Supa awesome!