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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
26,296 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 h...
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Top reviews

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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.

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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4801 - 4825 of 5,100 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 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 Paul

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Feb 9, 2025

Awesome course. I wish the course were explained better though. Andrew Ng's teaching is just spot on!

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