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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
32,127 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

DB

May 30, 2024

Great intro to supervised learning (regression & classification). Clear explanation of sigmoid function and decision thresholds. Could benefit from examples & exploring non-linear boundaries.

AA

Apr 29, 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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4626 - 4650 of 6,058 Reviews for Supervised Machine Learning: Regression and Classification

By mohammadreza e

•

Jul 22, 2023

Good intro to ML

By taleb s

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Jul 6, 2023

excellent course

By Isabella I

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Jul 4, 2023

Amazing teacher!

By arash g

•

Jun 30, 2023

Andrew is Great.

By Janith M

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Jun 24, 2023

very good course

By Andika R T

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Jun 21, 2023

very good course

By Hayk A

•

Jun 11, 2023

Excellent course

By PRABHAT S

•

Jun 11, 2023

Awesome course .

By Sadi T

•

May 29, 2023

very good course

By Mehedi H N

•

May 12, 2023

Best Course Ever

By Ioannis M

•

Apr 29, 2023

sehr gut erklärt

By Amirfazel K

•

Apr 20, 2023

It was very good

By Muhammad R

•

Apr 9, 2023

sangat menantang

By Nilufar M

•

Mar 26, 2023

its very useful

By Qiang C

•

Mar 4, 2023

wonderful class!

By Võ H

•

Feb 19, 2023

Amazing Course !

By George H

•

Feb 4, 2023

Excelent course.

By Mudasser A

•

Jan 12, 2023

Best Course Ever

By Hải N H

•

Jan 3, 2023

Very good course

By Daniel M

•

Dec 9, 2022

Excellent course

By MANISHA E E (

•

Nov 10, 2022

great experience

By Jadid

•

Nov 1, 2022

Very good course

By Prashant K

•

Oct 31, 2022

EXCILENT COURSE

By Amit C

•

Oct 13, 2022

Excellent pace.

By Eli H

•

Oct 11, 2022

Very great intro