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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 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.

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.

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4651 - 4675 of 6,057 Reviews for Supervised Machine Learning: Regression and Classification

By 朱志豪

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Sep 11, 2022

非常的细致、生动，绝非浪得虚名！

By songjiale

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Sep 9, 2022

very good class

By phuong a d

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Aug 16, 2022

Excellent Course

By abdul h

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Aug 10, 2022

Best Best Best!

By Tianxiu Z (

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Aug 9, 2022

Basic and handy.

By Aiyedun R

•

Aug 6, 2022

Very explanatory

By arian d

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Jul 27, 2022

best course ever

By Aishwarya S

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Jul 25, 2022

AMAZING. PERIOD.

By Benedict N Y E

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Jul 25, 2022

like the quizzes

By Jim R

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Jul 22, 2022

Very well done.

By Susmit S

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Jul 14, 2022

Loved the course

By Aquiles B

•

Jul 14, 2022

Excellent Course

By 文军 彭

•

Jun 29, 2022

Teach me a lot!

By Eloy H R

•

Feb 20, 2026

muy interesante

By Matias R C

•

Dec 1, 2025

superbuen curso

By deenaa P

•

Sep 29, 2025

best instructor

By Tomás T

•

Sep 16, 2025

Amazing course!

By Amir R A

•

Jul 28, 2025

thank you sir .

By Mohd S

•

Jul 12, 2025

Great Course!!!

By Kiran

•

Apr 5, 2025

Best ML courser

By Kuchibatla B G

•

Mar 22, 2025

Fun learning AI

By Devang

•

Mar 21, 2025

Assume course !

By Samuel L

•

Feb 24, 2025

Exelente course

By Pedro L P

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Feb 20, 2025

Excelent Course

By Brijesh

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Feb 1, 2025

very impressive