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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
30,707 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.

AK

Jan 8, 2023

I learned a lot in this part and would like to continue further but one point that I would like to raise is that it would be better if you can tell us about the in general function that are used in ML

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4351 - 4375 of 5,812 Reviews for Supervised Machine Learning: Regression and Classification

By Mahdi F

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Dec 10, 2022

Awesome and useful

By Dat V N

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Oct 16, 2022

Good for beginners

By Akshay M

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Sep 28, 2022

Very insightful .

By Pragyansh S

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Sep 20, 2022

wonderful course.

By Madhu O P S

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Sep 6, 2022

I enjoyed course!!

By Vinay C

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Jul 30, 2022

Very well explain.

By Joaquin V

•

Jul 6, 2022

Easy to understand

By Leon Q

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Jun 29, 2022

Lab is very useful

By Killian P

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Jun 22, 2022

Very well taught !

By VAIBHAV S

•

Oct 15, 2025

very descriptive.

By Phil C

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May 29, 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 12, 2025

Excellent course!

By BIGYAN R

•

Mar 3, 2025

beginner friendly

By Lavanya

•

Feb 13, 2025

Excellent lecture

By Ankit D

•

Jan 27, 2025

Apt and Concise !

By Sena N E

•

Oct 26, 2024

Excellent course!

By Sachit S

•

Oct 24, 2024

Excellent course!

By Kunal M

•

Aug 4, 2024

too good to learn

By Manas D

•

Jul 8, 2024

Crisp and concise

By Safal B

•

May 14, 2024

Very great course

By Prayoga R S

•

Feb 27, 2024

Excellent course!

By Muhammed S

•

Feb 24, 2024

Thank you Andrew.

By Kunal

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Feb 18, 2024

loved the course!