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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
30,925 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.

DB

May 30, 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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4876 - 4900 of 5,862 Reviews for Supervised Machine Learning: Regression and Classification

By Anik D B

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Aug 6, 2024

very good!

By Michel B

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May 29, 2024

Good work!

By Michał D

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May 15, 2024

Very good!

By DaxoWiz '

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May 9, 2024

Magnifique

By An N K

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Mar 18, 2024

Meaningful

By Parsa N

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Mar 6, 2024

I love it!

By Ahmed A

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Feb 3, 2024

I love it!

By mojtabacode

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Feb 2, 2024

excellent.

By Zakaria F

•

Dec 29, 2023

impressive

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Dec 27, 2023

Amazing!!!

By Szu-Yao C

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Dec 19, 2023

Must Have!

By Claudio M A

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Aug 16, 2023

Excellente

By Bernard A

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Jul 31, 2023

The best !

By Abdul K

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Jul 17, 2023

just great

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Jul 16, 2023

perfectily

By Austing D

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Apr 23, 2023

Fantastic!

By Tomas B F A

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Apr 6, 2023

Excellent!

By David D Z

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Mar 18, 2023

Phenomenal

By Md. N S

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Mar 18, 2023

Excellent.

By Qaiser A

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Mar 17, 2023

VERY GREAT

By Hamza A

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Mar 2, 2023

Satisfied!

By Xueqi W

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Jan 3, 2023

Thank you!

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Jan 2, 2023

excellent.

By yuzhuobai

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Nov 26, 2022

Thank you!

By Pavan k C N

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Oct 14, 2022

very good