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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
28,368 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!!

AD

Nov 24, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

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3401 - 3425 of 5,425 Reviews for Supervised Machine Learning: Regression and Classification

By Mueed R

•

Nov 26, 2024

Best course available for starting AI

By Kandula S D

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Nov 13, 2024

A very good explanation by Andrew sir

By Aryan S

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Oct 23, 2024

Amazing course definitely recommended

By Maths f A

•

Oct 5, 2024

Really beneficial to the job seekers.

By Haoran F

•

Sep 9, 2024

Comprehensive & friendly for beginner

By Karolina g

•

Sep 5, 2024

muy bien explicado, facil de entender

By Hussain D

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Sep 4, 2024

I enjoyed it and loved the challenges

By Immanuel . A . D

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Jul 25, 2024

Very helpful especially for beginners

By Nathan G

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Jul 14, 2024

Amazing! Really easy to follow along!

By nachiket k

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Jul 7, 2024

one of the best teacher out there !!!

By Jovie C

•

May 20, 2024

very good course for machine learning

By Diamond G

•

Mar 25, 2024

Well explained and easy to understand

By zahra m

•

Mar 3, 2024

Great course for learning the basics!

By Muhammad A

•

Jan 19, 2024

History will never forget Andrew Sir.

By Amos

•

Jan 17, 2024

One of the best formats for learning!

By Huong P

•

Jan 8, 2024

easy to follow. very good instruction

By Andres S

•

Sep 22, 2023

Very didactic ! Perfect for beginners

By Anuj J

•

Sep 16, 2023

Must watch guide for machine learning

By Benjamin M

•

Aug 23, 2023

Very good course, I really recommend!

By Zafiq

•

Aug 1, 2023

Great insight on how the model works.

By Aryan V

•

Jun 1, 2023

Very informative and engaging course.

By Aaryan D

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May 25, 2023

An awesome intro to Machine Learning!

By Willian M

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May 6, 2023

Amazing training, highly recommended.

By yufei

•

Mar 31, 2023

helpful! A great thanks to Andrew NG!

By Arthur B S

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Mar 20, 2023

Ótimo curso para quem está começando.