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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
30,880 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

MA

Jan 28, 2025

I've really enjoyed learning about Machine Learning in such a guided way. It will continue to inspire me to learn more about AI. Thank you Andrew Ng, DeepLearning.AI, Standford ONLINE, and 糖心vlog官网观看.

AA

Apr 30, 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.

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3526 - 3550 of 5,849 Reviews for Supervised Machine Learning: Regression and Classification

By sambhav s

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Jan 2, 2025

Loved the maths part , labs are too good

By ZH W (

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Oct 1, 2024

very nice combination of math and coding

By T T V

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Sep 24, 2024

It is very fruitful. Highly recommended.

By Devendra J

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Jul 6, 2024

the best course for starting to learn ML

By Mario I E D

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Jul 4, 2024

Learning rate was as smooth as possible!

By Shanuka D

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Jun 4, 2024

One of the best courses I've enrolled in

By Shubham T

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Jun 1, 2024

The concept was taught very effectively.

By Josep M

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May 13, 2024

It is an introductory course. A good one

By random u

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Jan 9, 2024

Learned a lot in a short period of time.

By Reza F

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Jan 7, 2024

You are explaining simply! that's great!

By Abubakar A

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Dec 13, 2023

This is really a good experience for me.

By Bibit K

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Nov 18, 2023

Lab and course materials were crazy good

By Jancirubi K

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Nov 4, 2023

Excellent Instructor. Enjoyed learning..

By Yuchen D

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Oct 10, 2023

well-structured, straightforward,patient

By James H

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Sep 15, 2023

Really clear and friendly to beginner!!!

By John F

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Jul 27, 2023

Excellent pace and coverage of material.

By Omar A M M M

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Jul 27, 2023

excellent and neatly organized material!

By Yu K

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Jul 25, 2023

learnt a lot, lecturers are very patient

By AMIT K

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Jul 2, 2023

Very Nice Concept Understood by Andre ng

By Leo

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Jun 12, 2023

Excellent course ! Thank you very much !

By George J

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Mar 16, 2023

Great intro to machine learning concepts

By Patrick P

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Mar 15, 2023

A great course. Challenging, but doable.

By JUAN P P A

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Feb 9, 2023

Muy buen curso, el profesor es el mejor.

By Besufekad N

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Dec 31, 2022

Great topics and a great way of teaching

By Adam J

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Nov 6, 2022

Engaging content and helpful instruction