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

4.9
stars
30,880 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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4101 - 4125 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By KARANAM V K

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Jul 20, 2023

this is avery good course

By Youness E Y

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Jun 21, 2023

Great introduction to ML.

By SJin L

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Jun 4, 2023

Perfect online lecture!!!

By Prateek

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Jun 3, 2023

All very good and useful.

By Afdoni P S

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Apr 7, 2023

yoyoyoyoyooy marveloussss

By Adam d G

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Jan 30, 2023

Great overview of basics.

By Alec P

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Jan 8, 2023

The labs are my favorite!

By Harsh s

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Dec 27, 2022

good understanding course

By Eric T

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Sep 4, 2022

Thank you for the course

By Hyeon Y

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Aug 27, 2022

Great course! Thank you.

By Zeeshan K Y

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Aug 24, 2022

Thank you Deeplearning.ai

By Bảo T

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Jul 28, 2022

Nice and ez to understand

By Fazal K

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Jul 23, 2022

Good start for a beginner

By Aditya N G

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Jul 11, 2022

Great Learning Experience

By Pawan C

•

Jul 10, 2022

great learning experience

By Diana K

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Jul 14, 2025

Difficult but insightful

By Sarthak K

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Jun 11, 2025

Nothing from Everything!

By Yipeng L

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May 18, 2025

Very Good Lesson for me!

By HUỲNH H Đ

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May 9, 2025

That is a great lesson !

By SoundsForGamers

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Apr 16, 2025

Very interesting. Thanks

By Vikram A

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Mar 24, 2025

Was an very great course

By Mikhail T

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Mar 12, 2025

Absolutely great course!

By Renato A S

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Feb 21, 2025

sensacional so agradecer

By Kakali M

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Dec 9, 2024

experience was very nice