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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
25,815 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...
...

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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4776 - 4800 of 5,033 Reviews for Supervised Machine Learning: Regression and Classification

By Reza A

Jul 30, 2022

All the lectures are good. The only thing could be better is the assignments exercises.

By Purva T

Nov 29, 2023

Andrew Ng has explained every topic in depth and all lectures are easy to understand.

By SREEHARSH N

Jun 11, 2023

Great course for those who are looking to step into the world of machine learning!!!

By Rameshbabu

May 8, 2023

Great Training. Suggest to add one additional lectures to brush up the mathematics.

By Shashank A

Sep 13, 2024

The last portion(logistic regression) looks a bit rushed than the linear regression

By Eman M

Sep 23, 2023

Your lab session has timed out If you'd like to continue working, reopen the lab.

By Deleted A

Nov 29, 2022

There is no actual way to learn the basics of Python, you just CTRL+F other labs.

By 메타버스크리에이터

Mar 30, 2023

처음에는 조금 어렵고 뭐가 뭔지 몰랐지만 점점 익숙해지기 시작했습니다.. 앞으로 자주 방문해서 더 AI에 대한 더 많은 정보를 얻도록 하겠습니다

By Daniel N

Jul 12, 2022

Interesting, and useful, take on how the different topics relate to each other.

By Joshua E

Jun 12, 2023

The math can be confusing if you want to understand why the code is what it is.

By LALIT K

Oct 23, 2022

it was nice ,and with full touch of practical knowledge,it was really helpfull

By Sohrab M

Aug 29, 2022

I am really appreciated for being part of this community and learn new skills.

By ABHISHEK A

Jul 25, 2022

Great course but I wish instructor also explaned the option lap code as well.

By Gustavo T

Jul 21, 2022

Great content and learning pace. Just think the assignements could be harder.

By Mohd A A

Jan 25, 2025

Optional Labs would have been Interesting Only if they were not optional :-)

By mohammad m m

Jan 26, 2023

perfect, but mathematics and academics subject was lesser than it should be

By Fahad A

Jan 30, 2024

Overall the course is good but you should upgrade your labs;they are worse

By Thomas G

Feb 25, 2023

The programming style in the labs is much more complicated than necessary.

By Arindam P

May 31, 2024

Very well structured , well drafted and good difficulty level assignments

By Yashu A

Jun 21, 2023

it was an amazing course overall but I expected more mathematical details

By Magdy E

Feb 8, 2023

It's a good first step in Machine Learning and this course was so helpful

By Suvroneel N

Jan 8, 2024

labs were helpful but could've been better to explain the codes in video

By Tanish J

Aug 18, 2024

A little more of the underlying mathematics would have been appreciated

By michalis l

Dec 13, 2024

Great intro course The code assignments should may be more challenging

By Houimli M M

Feb 26, 2023

I strongly recommend this course as a first step in machine learning .