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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
31,651 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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4851 - 4875 of 5,974 Reviews for Supervised Machine Learning: Regression and Classification

By Ch V

•

Apr 29, 2023

Great Course

By bounphet t

•

Apr 15, 2023

great course

By Muhammad A R

•

Apr 11, 2023

very usefull

By Gautam S

•

Apr 2, 2023

Great Course

By Niranjana N

•

Apr 1, 2023

Great course

By Krish S

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Mar 18, 2023

Exceptional!

By manas d

•

Mar 16, 2023

very helpful

By Bharath S

•

Mar 7, 2023

mindblowing!

By Asma E

•

Mar 2, 2023

Good course.

By Alireza G

•

Feb 21, 2023

Great course

By Dominique C

•

Feb 6, 2023

just perfect

By aybars d

•

Jan 29, 2023

veery useful

By sohan p

•

Jan 25, 2023

Great course

By Fady S

•

Oct 13, 2022

great intro

By Gunaratne V

•

Oct 13, 2022

good course

By AOUJANA A

•

Oct 10, 2022

very useful

By Subhan N

•

Oct 6, 2022

Phenominal!

By Ali G

•

Sep 21, 2022

Magnificent

By Đạt N

•

Sep 5, 2022

good course

By Prathima

•

Sep 4, 2022

very helpful

By Ehsan [ G

•

Sep 1, 2022

Excellent!!!

By Angelo A

•

Aug 30, 2022

Great course

By Ruichen z

•

Aug 7, 2022

That's great

By A s

•

Jul 25, 2022

great course

By Đạt N

•

Jun 30, 2022

it's so good