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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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4201 - 4225 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Dhruv G

?

Nov 3, 2024

very helpful and basic

By Karen O

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Oct 16, 2024

?Excellent, thank you!

By Tuyen T

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Sep 12, 2024

Very interested course

By Laura M C

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Aug 27, 2024

Te da muy buenas bases

By Raj M

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Aug 10, 2024

Quite a bit intersting

By Youssef

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Jul 31, 2024

this course it helpful

By rana n

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May 21, 2024

it is very good course

By Vi?t T D

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May 18, 2024

Such a good ML course!

By Himanshu R

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Feb 28, 2024

Very good explanation.

By FAYCAL D

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Feb 21, 2024

best course i ever had

By BULENT G

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Feb 21, 2024

very good introduction

By Anannya M

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Jan 23, 2024

Andrew sir is the best

By Rakesh K

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Sep 26, 2023

Amazing teaching style

By Filya

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Sep 19, 2023

Thank You very much!!!

By Syed S A

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Sep 10, 2023

Excellently explained!

By Mazen K

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Aug 27, 2023

Highly Recommend this!

By Bodo C

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Aug 25, 2023

I enjoyed this course.

By ???

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Aug 17, 2023

What a useful lecture!

By Islam A

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Aug 1, 2023

The course is amazing.

By Deleted A

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Jul 30, 2023

Such a helpful course.

By Nicolas H

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May 27, 2023

Very well made course!

By Raghavendra K

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May 21, 2023

Excellent Explanation.

By M R

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May 18, 2023

It is simply excellent

By 陈曦

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Apr 9, 2023

very nice, keep moving

By S S

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Oct 25, 2022

A great start with ML