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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
30,836 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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By Amjad A G

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Dec 30, 2024

???? ???

By Pawan G

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Dec 9, 2024

Great!!!

By Piyush

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Dec 8, 2024

ml ka 14

By ANIKET B

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Nov 30, 2024

Great !!

By arham j

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Nov 17, 2024

its good

By Nicholas W

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Oct 24, 2024

Amazing.

By Prachet P

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Sep 21, 2024

Worthy!!

By 屈杰敏

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Aug 30, 2024

helpful!

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Aug 1, 2024

Amazing!

By K D

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Apr 26, 2024

The Best

By Karus H

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Mar 16, 2024

Amazing!

By Imrane G

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Feb 3, 2024

the best

By 鍾易達

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Dec 21, 2023

the best

By Abd a A N

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Nov 8, 2023

not easy

By 李嘉洋

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Sep 16, 2023

非常好，浅显易懂

By f_mirzaiy

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Jul 12, 2023

fabulous

By Ajaykumar J

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Jun 30, 2023

all good

By Anmol P

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Jun 28, 2023

Awesome!

By Muh. I A

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Jun 10, 2023

Amazing!

By Aladum K

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May 11, 2023

splendid

By Alireza T

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Apr 20, 2023

Awesome!

By 廖润龙

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Mar 28, 2023

易懂且讲的很深刻

By JuHo S

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Mar 26, 2023

goood!!!

By Hi?u N

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Feb 14, 2023

worth it

By Oluwasegun E

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Dec 23, 2022

Splendid