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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
22,170 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

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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

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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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2851 - 2875 of 4,542 Reviews for Supervised Machine Learning: Regression and Classification

By Aseem S

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Apr 9, 2023

THANKS FOR YOUR GUIDANCE! BEST COURSE!!

By mahmoud a

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Apr 8, 2023

veru excellent course .thanks very much

By Shahid H

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Apr 5, 2023

Best course i've ever studied regard ML

By Ackermann Y

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Mar 5, 2023

Very good course for complete beginers.

By YUCHEN O

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Jan 16, 2023

very good and let me love the ML field!

By Diaa h

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Jan 4, 2023

very useful course, thanks for the team

By Daud R

•

Dec 22, 2022

great course to start machine learning

By Maryam H

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Nov 21, 2022

so good, happy to attend this course :)

By 杨 罗

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Sep 8, 2022

学习机器学习最好的入门课程，完全能学懂，完全能学会。为未来的学习打下最好的基础

By Pablo G

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Jul 24, 2022

Great introduction to machine learning.

By Anton B

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Jul 6, 2022

Informative, clear, and very exciting!

By Imran R

•

Sep 11, 2024

I have learn a lot of things from here

By Racem D

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Aug 21, 2024

The BEST ML course I have taken so far

By Alejandro G

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Jun 28, 2024

I learned a lot with a moderate effort

By MD. M H

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Jun 12, 2024

Very nice and beginner friendly course

By Toghrul I

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May 23, 2024

Best course for theoretical foundation

By Leo R

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May 17, 2024

Very nice and very good explanations !

By Robert R

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Apr 6, 2024

Amazing course. Extremely well done.

By Yiqing W

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Apr 2, 2024

Informative, detailed and interesting.

By Ming Y

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Mar 25, 2024

Thanks Andrew, really a good course ~!

By vashu j

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Feb 10, 2024

very good if you can grab the concepts

By R V

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Feb 9, 2024

Loved the course very much. Wonderful.

By Asd 4

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Feb 7, 2024

thank you Andrew Ng thank you Stanford

By Abdullah A

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Sep 9, 2023

Perfect for beginners. Great course!!!

By Varshney T

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Aug 26, 2023

best course i have ever studied from .