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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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2901 - 2925 of 4,541 Reviews for Supervised Machine Learning: Regression and Classification

By Amos

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Jan 17, 2024

One of the best formats for learning!

By Huong P

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Jan 8, 2024

easy to follow. very good instruction

By Andres S

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Sep 21, 2023

Very didactic ! Perfect for beginners

By Anuj J

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Sep 16, 2023

Must watch guide for machine learning

By Benjamin M

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Aug 23, 2023

Very good course, I really recommend!

By Zafiq

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Aug 1, 2023

Great insight on how the model works.

By Aryan V

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Jun 1, 2023

Very informative and engaging course.

By Aaryan D

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May 25, 2023

An awesome intro to Machine Learning!

By Willian M

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May 6, 2023

Amazing training, highly recommended.

By yufei

•

Mar 30, 2023

helpful! A great thanks to Andrew NG!

By Arthur B S

•

Mar 20, 2023

Ótimo curso para quem está começando.

By Samuel G

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Dec 26, 2022

Thank you, this is an amazing course.

By Nikhil T

•

Nov 20, 2022

easy to learn with the help of videos

By Rene A D P

•

Oct 10, 2022

Incredible resource for learning ai.

By Ali I

•

Sep 28, 2022

Thanks alot for your fruitful coures.

By Talha K

•

Sep 7, 2022

Concise. Efficient. Beginner Friendly

By Mohamed O

•

Aug 25, 2022

very good course, and well organized.

By Kishore I

•

Aug 15, 2022

Excellent introductory course on ML.

By emirhan e

•

Aug 7, 2022

Thanks for this precious oppurtinity.

By Carlo D

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Jul 26, 2022

best intro course to machine learning

By Anush R A

•

Jul 12, 2022

best course to learn machine learning

By Daniel A

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Jul 11, 2022

Course very well executed. Thank you.

By Sayed M

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Jul 10, 2022

Thank you all for this amazing Course

By 黄金

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Jul 6, 2022

The lab part of the course is amazing

By Yuhao W

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Jul 4, 2022

better than before, with python coded