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

4.9
stars
24,409 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

FA

May 24, 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.

JM

Sep 21, 2022

Specacular course to learn the basics of ML. I was able to do it thanks to finnancial aid and I'm very grateful because this was really a great oportunity to learn. Looking forward to the next courses

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4476 - 4500 of 4,802 Reviews for Supervised Machine Learning: Regression and Classification

By Artem B

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Feb 12, 2023

The course material was outstanding; however, I found assignments not challenging enough. I was literally tasked to add a few lines of code to an existing code.

By Soham G

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Jul 14, 2023

Great course! Understood all the concepts and the fundamentals of ML but the lab sessions are a bit difficult to comprehend if you do not know python language.

By Leon H

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Oct 11, 2022

Very informative and well taught course. Only reduction in stars is due to the quizes being too easy and not accurately testing your knowledge of the subject.

By Ale M

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May 8, 2023

The Course is really good for theorical content, however I feel it might be lacking a little bit of practice.

The quizzes/ tests are really easy to pass, too.

By Jacob T

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Aug 29, 2022

Pretty useful, but I would have liked to seen more practice examples with actual code. I believe having someone to walk you through a lab is more beneficial.

By Sathyavardhan K

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Feb 14, 2024

I've understand the concept but here want add up on a lecture like how to implement those algorithm in python it will be easy to understand for a beginners

By Rahulan S

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May 24, 2023

The course was pretty hard. But the quizzes in the middle of the videos rly helped. I would recommend a bit more help with the python aspect of the course.

By Neha Y

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Jul 6, 2023

The lab work should not be fully solved. Or program should be left with question, formula and method explanation. Answers could be given after submission.

By Farouk B

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Sep 28, 2024

very good course but it needs lab practice , it looks like we just run the code , aand if we want to write by our self it is hard . but thank you so much

By Sebastian R

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Aug 24, 2022

Great introduction into machine learning, but I wish there were more options for practice rather than optional labs that are already completed for you.

By Muhammad T K

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Jul 6, 2022

This is a nice course. It gives a nice introduction to machine learning. The instructor is very nice at explaining concepts in easy to understand words.

By Sufiyan K

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Jan 8, 2024

The course is great and would have been much better if the optional labs had also been explained for a deeper understanding. Thank you for this course.

By MKLKEM T Y

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Feb 16, 2023

It is pretty good yet i wished if they made the optional labs not optional and concetrate at code live implementation, Anyways thank you NG for sharing

By Nachiketh G

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Mar 24, 2023

It was a bit too easy. I would have preferred more practical insights into the coding of these algorithms, as well as the theory behind the algorithms

By Mahmoud e

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Aug 29, 2023

thank you for this great course

in practice lab you do 30% from code and this is noot good you need to do 70% from code and they only 2 practice lab

By Boris B

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Jul 29, 2024

Very nice explanations. Even for people that already had machine learning as course I filled a lot of small gaps in my understanding and knowledge.

By Félix M

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Sep 10, 2023

Could use a bit more rigor in the assignments, but I appreciate the entry-level nature of it. Making ML accessible for most (realisticaly, not all)

By Aniket C

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Jul 13, 2022

I think it was a really good beginner course, but frankly, a bit slow at times (maybe a bit more could be added to really make it 3 weeks of work?)

By Hossein K

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Aug 14, 2023

Andrew's explanations were clear. I wish the course had a project or a homework assignment at the end of each week to have more hands-on practice.

By Saurabh K S

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Mar 1, 2023

This Course will would become more and more intresting and best if with concept explaining and CODE explanations of optional lab both will happen.

By MohammadAli A

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Dec 18, 2022

It was really good course.

but I preferred if it has more challenge to implement all the programs by ourselves and teach more about the codes.

By Ruedi G

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Aug 19, 2022

Excellent course. I had a bit technical difficulties with the notebooks. Error tracking is not as easy as in the system I ussually work with.

By Zaid A

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Jul 2, 2023

use scikit library as mandatory not optional. add lab that use the functions immediately not need to edit them. or use predict immediately.

By ISHFAQ B

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Aug 6, 2022

I would like to suggest to add lectures and explianations on importing libiraries and scripiting alos to amkemit more robust and independent

By Shravani K

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Apr 12, 2024

Everything it very well taught. In practice labs instead of utils another library should be used as it cannot run apart from their notebook