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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
32,078 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

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.

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.

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5876 - 5900 of 6,053 Reviews for Supervised Machine Learning: Regression and Classification

By Ghulam A

•

Nov 3, 2024

AMAZING EXPERIENCE

By JISAN A

•

Sep 29, 2023

Good for beginners

By Fawad A

•

Aug 6, 2023

This is best curse

By SYAMRAJ M

•

Sep 21, 2024

good explanantion

By Josef K

•

May 15, 2025

perfect training

By Deepak R

•

Jul 11, 2022

very nice course

By Silvia G

•

Jan 13, 2026

silvia gagliano

By Thiện N

•

Sep 16, 2022

Good knowledge

By Madhul K

•

Aug 8, 2022

Great learning

By Somtirtha D

•

Jan 9, 2024

Great course.

By Juan E

•

Jul 29, 2023

g,mbvscMbn<MA

By Rahul C

•

Nov 4, 2025

Great Course

By Madan

•

Aug 13, 2023

Great course

By Echekwu E

•

Aug 6, 2022

Fundalmental

By Vishal B

•

Nov 10, 2023

nice course

By Veerendra P

•

Sep 17, 2023

NIce Course

By Kevin S

•

Jun 25, 2024

Fast paced

By Salahuddin S

•

Jan 25, 2024

it is good

By Kenny P L

•

Mar 1, 2026

Excelente

By Haseeb A

•

Jul 1, 2025

Fantastic

By 22501A4452 P P R

•

Jul 27, 2024

Very good

By luficerg f

•

Jun 5, 2023

Very good

By Nikhil N M

•

Aug 16, 2022

Very Nice

By Aki

•

Aug 12, 2022

Very good

By Ahmed H M

•

Aug 10, 2025

great