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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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4501 - 4525 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By Ali A

•

Jul 23, 2023

A wonderful course

By Samy M (

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Jul 6, 2023

very useful course

By Huỳnh T T

•

Apr 17, 2023

Good for beginners

By Ashutosh B

•

Mar 13, 2023

Best for beginner.

By Minh T D

•

Mar 1, 2023

Great introduction

By SADEEM A N A

•

Dec 13, 2022

good Learning

👍🏻

By Mahdi F

•

Dec 11, 2022

Awesome and useful

By Dat V N

•

Oct 17, 2022

Good for beginners

By Akshay M

•

Sep 29, 2022

Very insightful .

By Pragyansh S

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Sep 20, 2022

wonderful course.

By Madhu O

•

Sep 6, 2022

I enjoyed course!!

By Vinay C

•

Jul 30, 2022

Very well explain.

By Joaquin V

•

Jul 7, 2022

Easy to understand

By Leon Q

•

Jun 29, 2022

Lab is very useful

By Killian P

•

Jun 22, 2022

Very well taught !

By Md. R M ,

•

Feb 4, 2026

Very interactive.

By SIDDHARTH P

•

Dec 2, 2025

Best one to exist

By Amr K

•

Nov 30, 2025

excellent content

By Cochet F

•

Oct 29, 2025

Andrew the goat !

By VAIBHAV S

•

Oct 16, 2025

very descriptive.

By Phil C

•

May 30, 2025

Excellent design.

By Bằng L V

•

May 24, 2025

it's good program

By Thanh L N

•

Apr 23, 2025

very good!!!!!!!!

By Tuhin D

•

Mar 13, 2025

Excellent course!

By BIGYAN R

•

Mar 3, 2025

beginner friendly