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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
18,908 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

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

AD

Nov 23, 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.

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3651 - 3675 of 3,908 Reviews for Supervised Machine Learning: Regression and Classification

By Manikandan E

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Jul 10, 2022

Great course in Machine Learning for begineers, still required more details and topics which are required to be known for a begineer to get the solid understanding in ML

By Anmol S

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Jan 8, 2023

It was a good pleasure to learn algorithms from Sir Andrew Ng and stanford University. The Content in the course was very Easy and the concept were made crystal clear.

By akram a

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Nov 6, 2023

Andrew ng teaching was excellent. In my opinion, it is better if the exercises are harder and the number of topics covered in each section is Increased. thanks a lot

By Ian R

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Sep 5, 2022

Good explanation of concepts. Assignments were straightforward for someone with modest Python experience. This first fragmetn of the original ML course felt short.

By Khushi S

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Mar 18, 2023

This course is great if you have a basic understanding of ml topics and want to go deeper into the theory or even if you want to know what actually is going on.

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 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 Talha 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 محمود م م ع ا ا

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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 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.