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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
25,432 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

JM

Sep 21, 2022

Specacular course to learn the basics of ML. I was able to do it thanks to finnancial aid and I'm very grateful because this was really a great oportunity to learn. Looking forward to the next courses

AD

Nov 23, 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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3276 - 3300 of 4,976 Reviews for Supervised Machine Learning: Regression and Classification

By JL

•

Nov 29, 2023

easy to understand all the things

By Jin

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Nov 3, 2023

Great learning materials! Thanks!

By Vishal K G

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Oct 14, 2023

loved it.. very nice explanation.

By Fahrul A N

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Oct 5, 2023

Andrew Ng is the best instructor!

By Mohit K

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Sep 13, 2023

The Way of explaining is too good

By Tiong W

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Aug 26, 2023

help to build my basics stronger.

By Everton D

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Aug 15, 2023

Difficult but excellent course!!!

By Muttakin K

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Aug 12, 2023

A very good course for begineers.

By Emin A

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Jul 29, 2023

very entertaining and educational

By Hemanth S

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Jul 17, 2023

Best Course for Machine Learning.

By PRAVEEN S

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Jun 5, 2023

An excellent introductory course.

By Jean F

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Apr 14, 2023

Great course, highly recommended.

By Cuong P C

•

Feb 25, 2023

Thanks for the great instruction.

By Long T B

•

Dec 28, 2022

Andrew is the best ML instructor.

By Rameez A

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Dec 25, 2022

Knowledge gained is just Amazing.

By Onwunyi C

•

Oct 18, 2022

Wonderful and challenging course

By Debi R

•

Sep 29, 2022

it is the course for everyone...

By Meysam M

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Sep 27, 2022

I appreciate it. It was awesome.

By Yugal K

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Aug 16, 2022

Very informative and interactive.

By Julio A L C

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Aug 6, 2022

Lovely course, I learned so much!

By Birhanu G

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Aug 2, 2022

Best course for machine learning.

By Syed A n

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Jul 24, 2022

Very Clear and in depth learning.

By Hardy W

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Jul 21, 2022

pretty straightforward and clear!

By RAHUL R

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Nov 6, 2024

First step into the ocean of AI.

By Mohamed Y

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Oct 28, 2024

Thank you Andrew and coursera <3