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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
28,003 ratings

About the Course

In the first course of the Machine Learning Specialization, you will: 鈥� Build machine learning models in Python using popular machine learning libraries NumPy and scikit-learn. 鈥� 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鈥檚 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鈥檙e 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

FA

May 25, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

AD

Nov 24, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

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3726 - 3750 of 5,355 Reviews for Supervised Machine Learning: Regression and Classification

By Harshit K

鈥�

Nov 25, 2023

best course available in ML

By Omer N

鈥�

Sep 10, 2023

Exceptionally great teacher

By marwa o

鈥�

Jul 23, 2023

very simple and easy course

By Nandan K

鈥�

Jul 21, 2023

please include some project

By Muhammad H M

鈥�

Jul 11, 2023

Great concepts and learning

By Aditya G

鈥�

Jul 8, 2023

really good for beginners!!

By Derek 鍏�

鈥�

May 20, 2023

easy to understand! love it

By Abiton P

鈥�

May 18, 2023

best start up for beginners

By Md. Z G

鈥�

May 13, 2023

Best beginner friendly one.

By Vedant N

鈥�

Mar 16, 2023

It war really good course .

By Hiren K

鈥�

Mar 15, 2023

Thanks Professor Andrew Ng.

By R谋fat u

鈥�

Mar 13, 2023

It was a very useful course

By Tianyue P

鈥�

Jan 7, 2023

Wonderful course for basics

By GAURAV M

鈥�

Nov 8, 2022

Amazing learning experience

By Sundar R C

鈥�

Sep 19, 2022

Good informative Course !!

By MUHAMMAD A

鈥�

Aug 21, 2022

For every beginner student.

By amr m

鈥�

Aug 10, 2022

iam very thankful mr andrew

By Tulkin Y

鈥�

Aug 6, 2022

I really liked this course!

By Felipe d L P

鈥�

Jul 9, 2022

Incredible amazing course!

By Farrel H

鈥�

Mar 20, 2025

Having a great experience!

By Fatih A

鈥�

Jan 12, 2025

It was an excellent course

By Fakhrutdinov A

鈥�

Jan 4, 2025

most interesting ML course

By Jiang X

鈥�

Jan 1, 2025

Easy to understand and use

By Avishek C

鈥�

Nov 26, 2024

Phenomenal course it is...

By BIKRAM S

鈥�

Nov 10, 2024

IT IS BEST FOR NOOBS IN ML