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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

MR

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Teaching is an art and Andrew Ng is a great artist. He explained everything in the course in the details and with examples easy to comprehend. Thanks a lot for helping thousands of students like me.

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2951 - 2975 of 4,570 Reviews for Supervised Machine Learning: Regression and Classification

By Sahan L

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Jan 13, 2024

Excellent and very inspiring course.

By Tanvir A S

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Dec 20, 2023

A wonderful course making ML easier.

By Emre G

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Oct 9, 2023

amazing course, had amazing insights

By Seyed K M Z

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Sep 7, 2023

a great course to start learning ML!

By ekins K

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Aug 4, 2023

Excellent course, beginner friendly.

By Mahan S

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Jul 24, 2023

that was a great and helpful course.

By hossein t

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Jul 6, 2023

andrew ng is really a great teacher.

By Anaj P

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Jun 28, 2023

this course is ideal for ml beginner

By Nawaraj K

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May 31, 2023

Great course and great instructor!!!

By Thomas T

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May 10, 2023

Best ML course available in Coursera

By Sharif M

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May 4, 2023

Very Simple and informative course

By Justin H

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Feb 11, 2023

Andrew Ng == champion ML instruction

By Ruttanan R

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Dec 26, 2022

Andrew Ng is a really great teacher!

By Xiaodie L

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Nov 3, 2022

Easily understand and useful course!

By Velizar T

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Oct 9, 2022

Great explanations and lots of fun!

By Jeffrey S

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Aug 29, 2022

Excellent Course, Highly recommended

By YiÄŸit T

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Aug 17, 2022

Very easy to understand, great job.

By Fateh M

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Jul 31, 2022

Perfect, as expected from Andrew. Ng

By Md. R H

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Jul 10, 2022

Very effective and wonderful course.

By Banriskhem K

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Jul 9, 2022

Programming assignments are too easy

By Juan D C

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Sep 16, 2024

Great Intro and practical examples.

By El H A S

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Jul 20, 2024

Really nice course, thanks Andrew^^

By Nikhil R

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Jul 11, 2024

Learnt A Lot......Thanks Andrew sir

By Greeshma J

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Jun 29, 2024

Best beginner friendly ML course...

By Hong D

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Apr 25, 2024

The course layout is easy to follow