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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
26,536 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

AD

Nov 24, 2022

Amazingly delivered course! Very impressed. The concepts are communicated very clearly and concisely, making the course content very accessible to those without a maths or computer science background.

FA

May 25, 2023

The course was extremely beginner friendly and easy to follow, loved the curriculum, learned a lot about various ML algorithms like linear, and logistic regression, and was a great overall experience.

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3201 - 3225 of 5,146 Reviews for Supervised Machine Learning: Regression and Classification

By soujan n

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Dec 25, 2024

Great insights for conceptualizing AI.

By Nawar S

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Nov 17, 2024

The course very informative and clear.

By Nour E

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Oct 24, 2024

Really thought through and informative

By Imran R

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Sep 12, 2024

I have learn a lot of things from here

By Racem D

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Aug 21, 2024

The BEST ML course I have taken so far

By Alejandro G

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Jun 28, 2024

I learned a lot with a moderate effort

By MD. M H

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Jun 12, 2024

Very nice and beginner friendly course

By Toghrul I

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May 23, 2024

Best course for theoretical foundation

By Leo R

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May 18, 2024

Very nice and very good explanations !

By Robert R

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Apr 6, 2024

Amazing course. Extremely well done.

By Yiqing W

•

Apr 2, 2024

Informative, detailed and interesting.

By Ming Y

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Mar 25, 2024

Thanks Andrew, really a good course ~!

By vashu j

•

Feb 10, 2024

very good if you can grab the concepts

By Viswa R

•

Feb 9, 2024

Loved the course very much. Wonderful.

By Asd 4

•

Feb 7, 2024

thank you Andrew Ng thank you Stanford

By Abdullah A

•

Sep 9, 2023

Perfect for beginners. Great course!!!

By Varshney T

•

Aug 26, 2023

best course i have ever studied from .

By Sepehr M

•

Aug 16, 2023

Was a good course to start the journey

By Johanna D A

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Aug 4, 2023

excellent course, congratulations !!!!

By Bikesh S

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Aug 4, 2023

great course to start maching learning

By Subham G

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Jun 9, 2023

Very good course for Machine Learning!

By Neha D

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May 31, 2023

Very Nice course.

Highly understandable

By Yamil A

•

May 19, 2023

very well content along of this course

By Pedro P H

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May 10, 2023

Very clear, step by step explanations.

By Shubham B

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Feb 6, 2023

This is exactly what I am looking for.