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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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4776 - 4800 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By 膼岷 N

鈥�

Sep 5, 2022

good course

By Prathima

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Sep 4, 2022

very helpful

By Ehsan [ G

鈥�

Sep 2, 2022

Excellent!!!

By Angelo A

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Aug 31, 2022

Great course

By Ruichen z

鈥�

Aug 7, 2022

That's great

By A s

鈥�

Jul 26, 2022

great course

By 膼岷 N

鈥�

Jun 30, 2022

it's so good

By Sanchit J

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Jun 29, 2022

Great Course

By ALI A

鈥�

Nov 9, 2025

best course

By Varun N G .

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Sep 25, 2025

Nice course

By Ng么 T T

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Sep 8, 2025

good course

By Valeria C M

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Aug 25, 2025

Really nice

By putra f

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Aug 7, 2025

best course

By Osman B

鈥�

Aug 4, 2025

good course

By Vivek S

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Jul 19, 2025

Its perfect

By Ibrahim J H

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Jun 16, 2025

Best of all

By Samba B K

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May 26, 2025

Excellent !

By Carlos R d S R

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May 3, 2025

脫timo curso

By john_ d

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Apr 17, 2025

exceptional

By MD. N H J S 2

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Apr 5, 2025

Best course

By Mudit C

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Mar 23, 2025

Amazing !!!

By ASHWANTH S K C

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Jan 22, 2025

best course

By Aneesh P

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Dec 22, 2024

Really good

By Pradeep Y

鈥�

Dec 9, 2024

very helpul

By Prathmesh K

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Nov 19, 2024

best course