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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
32,240 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 29, 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.

MA

Sep 17, 2024

I learned a lot from this specialized course. It was one of the best courses that I've ever done. The instructor i.e. Andrew Ng taught every concepts so well. I'll highly recommend others to do this.

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By Quoc V N

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Oct 27, 2023

oke \

By Joel E

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Oct 16, 2023

bueno

By Muhammad R P S

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Oct 16, 2023

great

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Oct 5, 2023

magic

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Sep 20, 2023

good.

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great

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great

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Good!

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Great

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Mar 8, 2023

great

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Dec 1, 2022

great

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Nov 19, 2022

goood

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Nov 17, 2022

great

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good

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Oct 8, 2022

good

By Garima S

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Oct 7, 2022

NICE

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Oct 2, 2022

good

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Sep 28, 2022

Good

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Sep 21, 2022

great

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Aug 22, 2022

great

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Great

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Jun 30, 2022

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By Ayush S

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Feb 17, 2026

Good