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Learner Reviews & Feedback for Supervised Machine Learning: Regression and Classification by DeepLearning.AI

4.9
stars
30,785 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

ED

Apr 14, 2025

Loved Andrew Ng's videos and the hands on Jupyter notebook labs! My understanding of ML has significantly improved thanks to this course and going on to the next course to complete ML specialization!!

JG

Apr 27, 2024

Es un curso diferente a los de regresión y clasificación donde solo se enfocan en aplicar los algoritmos de Scikit-learn. El profesor Andrew le da un enfoque profundo al detrás que hay en cada modelo.

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3151 - 3175 of 5,826 Reviews for Supervised Machine Learning: Regression and Classification

By Walter M M

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Apr 29, 2024

Excelente! Codigo y matematica muy bien explicados

By Luciano D

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Apr 8, 2024

Very broad set of concepts and learning modalities

By Michael S

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Mar 9, 2024

Outstanding course for machine learning beginners!

By Ti R S

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Dec 25, 2023

Very very good :D I'm making my own ml library now

By Hugo C

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Nov 8, 2023

Fantastic introductory course from Andrew and team

By Akshith G

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Nov 2, 2023

I Have learned many Topics in the Machine Learning

By Yuhong H

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Sep 19, 2023

Great lectures and lab, Andrew is a great lecturer

By Anatoliy B

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Sep 16, 2023

Very well prepared course. Thanks Andrew and team.

By ghassen f

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Sep 12, 2023

well explained for any level of math/coding skills

By Pollab K R

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Aug 31, 2023

nice course. I have learned lots from this course.

By Daniel L

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Mar 21, 2023

perfect for getting something extra under you belt

By javier b

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Mar 19, 2023

Great course to iniciate in this amazing ML world!

By Hariom C

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Mar 15, 2023

A helpful course to begin with machine learning...

By Danish M

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Mar 3, 2023

very excellent course ,mathematical concepts clear

By Vinayak V

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Jan 31, 2023

Very very much needed basics to any data scientist

By Daniel S

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Jan 12, 2023

Started easy, and finished hard. Fantastic course!

By Mert C

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Dec 26, 2022

Andrew NG makes complex topics easy to understand.

By Pranavdeep S

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Oct 26, 2022

Thank you professor for such an enriching course.

By Btsn

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Aug 16, 2022

great course ever . i would like to say thank you.

By BOUSSAHLA O

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Jul 25, 2022

The best course to start learning machine learning

By Elizabeth S O

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Jul 19, 2022

Explanations are intuitive and easy to understand!

By Karan S

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Jul 21, 2025

nice, informational and does make you write code.

By IMANE J T

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Apr 12, 2025

je vous remercie pour cette très bonne formation.

By David P

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Jan 29, 2025

Great content, easy to understand, thanks Andrew!