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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

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.

DB

May 31, 2024

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

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4601 - 4625 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Bakhtiyor

鈥�

Dec 31, 2023

awesome course

By HIMANSHU B 2

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Dec 27, 2023

awesome course

By Souvik M

鈥�

Dec 11, 2023

Great Learning

By Md A I

鈥�

Nov 27, 2023

Helpful Course

By Nitin W

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Nov 22, 2023

Amazing Course

By Anass A

鈥�

Nov 16, 2023

really amazing

By jony k

鈥�

Oct 27, 2023

very very good

By 袗泄薪褍褉 袛

鈥�

Oct 23, 2023

袩芯谢械蟹薪褘泄 泻褍褉褋!

By Cheater F

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Aug 23, 2023

great Courses.

By Nithin B

鈥�

Aug 22, 2023

well explained

By Soumit R

鈥�

Aug 14, 2023

Best ml course

By Mohammadreza J J

鈥�

Jul 15, 2023

I'm so excited

By saparapu r

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Jul 5, 2023

corse was good

By V农 H

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Jun 26, 2023

Excellent!!!!!

By SUBRATA M

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Jun 25, 2023

very very good

By Satish s M

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Jun 16, 2023

very effective

By legendsof c

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Jun 12, 2023

Very helpful 鈾�

By Deleted A

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May 31, 2023

awesome course

By Aisha A

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May 29, 2023

Amazing course

By Prasanth K A S

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May 8, 2023

awesome course

By George F

鈥�

May 8, 2023

thank u Andrew

By Yvan P

鈥�

Apr 17, 2023

the best intro

By anna k

鈥�

Feb 16, 2023

Great content!

By Adil M

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Feb 1, 2023

Very elaborate

By Ansh P

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Jan 22, 2023

Amazing for me