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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
29,496 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 14, 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 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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5276 - 5300 of 5,610 Reviews for Supervised Machine Learning: Regression and Classification

By Moutassi B G

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Sep 1, 2024

The basics are perfectly and so simply explained and all is done such you must understand what you are studying

By Shiva T

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Feb 20, 2023

Some more practical examples can be included but the course material and topics and ecplaination were great.

By Amit S

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Dec 18, 2022

Every concept was explained in a very easy and interesting way. Really liked the course and way of teaching.

By Anukul D

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Nov 10, 2022

I actually got the right course at right time and thank you to coursera for providing the course. Hats Off!!

By Raman K P

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Dec 18, 2022

Real life dataset use would have been more helpful.

Also, use of scikit-learn could have been explored more.

By Kunal G

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Aug 16, 2022

Good One, the course is to the point . Please include linear algebra as it was added in the older version .

By Royston L

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Jun 21, 2022

I don't understand why the practice lab code for gradient descent and the lab assignment code is different.

By Fang H

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Jan 24, 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 Kartik T

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Jul 25, 2025

It would be better if we could get the downloaded notes of what the Mr. Andrew Ng is showing in the ppt.

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.