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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
27,808 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

ED

Apr 13, 2025

Loved Andrew Ng's videos and the hands on Jupyter notebook labs! My understanding of ML has significantly improved thanks to this course and going on to the next course to complete ML specialization!!

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.

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5026 - 5050 of 5,328 Reviews for Supervised Machine Learning: Regression and Classification

By Fang H

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Jan 23, 2024

Explained the complex concepts in very clear and simple way. Labs are very helpful and very well designed.

By Samuel S

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Jul 16, 2022

It get's exponetially harder as the weeks go by. This course could really use more programming excercises!

By Alzahra A A

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Jul 21, 2023

A great course, very informative and easy to understand.

Wish there were more project based assignments.

By parsa r

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Jul 23, 2024

great course. Dr Andrew ng explain very simple and perfect. but i wish it had more mathematical terms.

By Ryan H

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Jun 29, 2023

Weeks 1 and 2 were great. Week 3 got a little complicated and seemed a bit esoteric... But very happy.

By Sai D N

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Jul 12, 2022

It an introduction to ML. Course flow is fantastic and assignments are important to learn the content.

By Nikhil J

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Sep 5, 2022

It is a nice course , from this i learned what is regression and classifications in machine learning

By Santhosh R K R

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Sep 18, 2024

Excellent teaching i thoroughly enjoyed learning and getting started with the machine learning field

By Nikita

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Jun 13, 2023

I wish there were more practice tasks. But this course gives you good understanding of the concepts.

By Ans S

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Mar 29, 2024

Best for learning deep concepts and mathematics inside but not sufficient for the job ready skills.

By Manasvini G

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Nov 1, 2024

Loved the way instructor Andrew Ng delivered the concept. Practical knowledge can be poured more.

By Marc A

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Jun 5, 2024

The labs are not very challenging, maybe some more coding would help to understand more material.

By Oliver M

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Nov 21, 2022

The derivations of some of the algorithms could have been covered, just for better understanding.

By Alankrit R

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Apr 25, 2024

this course lacks a little bit in explaining the python implementation of the concepts taught.

By Hammad R

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Aug 28, 2023

The course teacher has the same tone all over the course hence makes me fall asleep and tired.

By Bisa V

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Oct 17, 2022

Really very easy to learn and the professor also explained the concepts from the basic level.

By Stephen T

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Jun 25, 2024

Useful introduction to Supervised Machine Learning, including Linear and Logistic Regression

By jaasim m

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Feb 27, 2024

the transition from basic to advanced could be more gradual.but the classes are really good.

By Yash S

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Jan 24, 2024

Well designed and well explained. The coding assignments and optional labs were also great.

By PRAMIDI V S S S

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Jan 15, 2025

Found very useful thank you Andrew Ng sir and thank you coursera for bringing this content

By Sharif R

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Oct 5, 2024

This was the most easily understanding course. Making the tough topics of ML in easy words

By Mohammad F K

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May 29, 2024

So much details about each and everything. A very fine way of teaching. Thanks Sir Andrew!

By David I

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Dec 7, 2022

The course is great. I would prefer for there to be more coding involved from the student.

By Alberto C

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Oct 14, 2024

Great course, it would have been even better to have more practical questions to work on.