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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: ? 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

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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4826 - 4850 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Akitha M A

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Jul 10, 2023

Best course

By ANIKOOL S

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Jun 27, 2023

good course

By Kishan S L

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Jun 11, 2023

Good Course

By vinayak

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May 28, 2023

The best!!!

By faisal a

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Apr 29, 2023

nice course

By mahan s

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Apr 12, 2023

wonderfulll

By Yashvardhan S

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Mar 21, 2023

good course

By Muhammad H M

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Feb 25, 2023

Best Course

By Amrutha S

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Jan 29, 2023

Very useful

By Kaitlyn H

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Jan 1, 2023

Super Good!

By Moema R P d O

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Dec 28, 2022

Excellent!!

By 周伟帆

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Dec 15, 2022

是一门非常好的入门课程

By Parth D

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Nov 27, 2022

Top Notch !

By Ahmed Y

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Nov 6, 2022

Great work

By Tseung-ho C

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Oct 30, 2022

Very Good!

By Emily C L

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Oct 23, 2022

It's great!

By Mahmoud E

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Oct 21, 2022

successful

By Mohammad F

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Oct 12, 2022

Very Good.

By ???

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Sep 30, 2022

very good!

By VANDAN R

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Sep 6, 2022

NIce course

By Luqmaan A

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Sep 3, 2022

masterpeice

By Prathamesh K

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Aug 20, 2022

best course

By Amol A

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Aug 13, 2022

Exceptional

By Mohamed A

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Aug 11, 2022

very useful

By Khaled E E

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Oct 16, 2025

very great