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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
30,836 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 30, 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 31, 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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3751 - 3775 of 5,846 Reviews for Supervised Machine Learning: Regression and Classification

By Amir-Ali M

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Jul 30, 2022

Phenominal course for entering AI.

By Hasibul H

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Jul 18, 2022

One of the best course of 糖心vlog官网观看

By Xinyue L

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Jul 15, 2022

A really good high level overview!

By Sixto M

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Oct 31, 2025

Excelente el docente y el material

By Sidney H

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Oct 15, 2025

I need to take Python & Satistics

By ESHITHA K

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Sep 28, 2025

Very Usefull ML motivated students

By Ho M D

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Aug 1, 2025

Perfect start for machine learning

By JW

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Jun 26, 2025

Excellent Machine Learning Course!

By Suhaib V

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May 30, 2025

I gained many knowledge, Thank You

By Anshuman N

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Mar 21, 2025

Very Good beginner friendly course

By Ibrahim K

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Dec 24, 2024

Amazing explanations and breakdown

By Gajendra K .

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Dec 18, 2024

Teaching method is very excellent.

By Bách C V

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Sep 12, 2024

This course is beginner friendly !

By Harihara s R

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Aug 25, 2024

very helpful thanks for the course

By pritam d

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Aug 18, 2024

Great course. I have learnt a lot.

By Abigail L

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Jul 28, 2024

老师讲得非常好，有趣生动，对我学习机器学习入门帮助真的很大，受益匪浅

By Flávio N

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Jun 20, 2024

Excelente conteúdo, otima didatica

By Saagar T

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May 30, 2024

Perfectly paced and soft lectures.

By Mayank G

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May 20, 2024

Thanks For Delivering Good Content

By Robert P

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May 17, 2024

A good start for my learning plan.

By Yousef A

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Feb 27, 2024

very great course so much to learn

By William T

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Dec 20, 2023

Much better vs the old Octave days

By Pruthviraj C

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Dec 4, 2023

Best! can't expect more than this!

By YALALA V V

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Nov 23, 2023

Excellent course and explanation!!

By Tikhon B

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Nov 13, 2023

Amazing and easy to follow course!