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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
32,121 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 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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4201 - 4225 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By Mazhar I

•

Jul 25, 2022

Highly recommanded .......

By Sam S

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Sep 29, 2025

Andrew Ng sir nailed it!!

By Ashish k

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May 23, 2025

Great Learning Experience

By Jacques-Antoine D

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Feb 26, 2025

Excellent videos and labs

By Romain D

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Sep 27, 2024

Very clear and insightful

By Pranav S

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Sep 21, 2024

Very quality of knowladge

By prabhjot s

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Jul 23, 2024

excellent teaching skills

By Jatin S

•

Jun 30, 2024

Best course for beginners

By Sarthak A

•

May 21, 2024

thanku andrew ng for this

By Abdullah D

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Mar 25, 2024

Thank you for everything.

By Avishkar P

•

Feb 29, 2024

covers solid fundamentals

By Onkar K

•

Feb 6, 2024

Andrew ng is best teacher

By Lakshay S

•

Dec 28, 2023

Very well designed Course

By Henrique V D H

•

Dec 8, 2023

Great introductory course

By Carlos A

•

Sep 7, 2023

Great course! super worth

By KARANAM V K

•

Jul 20, 2023

this is avery good course

By Youness E Y

•

Jun 22, 2023

Great introduction to ML.

By SJin L

•

Jun 4, 2023

Perfect online lecture!!!

By Prateek

•

Jun 4, 2023

All very good and useful.

By Afdoni P S

•

Apr 7, 2023

yoyoyoyoyooy marveloussss

By Adam d G

•

Jan 31, 2023

Great overview of basics.

By Alec P

•

Jan 9, 2023

The labs are my favorite!

By Harsh s

•

Dec 28, 2022

good understanding course

By Eric T

•

Sep 4, 2022

Thank you for the course