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Learner Reviews & Feedback for Multiple Linear Regression with scikit-learn by Coursera Project Network

355 ratings

About the Course

In this 2-hour long project-based course, you will build and evaluate multiple linear regression models using Python. You will use scikit-learn to calculate the regression, while using pandas for data management and seaborn for data visualization. The data for this project consists of the very popular Advertising dataset to predict sales revenue based on advertising spending through media such as TV, radio, and newspaper. By the end of this project, you will be able to: - Build univariate and multivariate linear regression models using scikit-learn - Perform Exploratory Data Analysis (EDA) and data visualization with seaborn - Evaluate model fit and accuracy using numerical measures such as R² and RMSE - Model interaction effects in regression using basic feature engineering techniques This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, this means instant access to a cloud desktop with Jupyter Notebooks and Python 3.7 with all the necessary libraries pre-installed. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

Top reviews


Sep 15, 2020

This project is great. Clearly explained and well delivered. I will highly recommend to take this project. The instructor is great!


Feb 7, 2021

Well paced, very informative, I felt I learnt skills that I can apply to practical problems immediately.

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26 - 50 of 55 Reviews for Multiple Linear Regression with scikit-learn

By Pulluri R

May 6, 2020



Sep 16, 2020


By tale p

Jun 26, 2020


By p s

Jun 25, 2020


By Vajinepalli s s

Jun 16, 2020


By Abhishek P G

Jun 15, 2020


By Katamreddy M r

Jun 27, 2020



Jul 1, 2020

The course is well structured and all the important theories and concepts have been explained in a quite detailed fashion. One should definitely try out this course to strengthen their skills in foundational level machine learning.

By Nikhil T

Jul 6, 2020

This course who wants to learn about basics and he has made it understand quite fine and apart from it quiz is very easy so you will pass but i would request him to atleast have 2 or more examples it would be much more better

By Shubham A

Apr 15, 2020

Great course. Thanks to the instructor, The rhyme platform is sometimes very slow, content: (7/10),Audio clarity: (5/10), video clarity: (8/10), Rhyme platform performance: (4/10).


Apr 17, 2020

Very good for freshers. Discussed the basic concepts and implemented them. They have a virtual computer so you need not install or download anything.

By Isah A

Nov 24, 2020

Nice project for beginners. In the last video, there was a very useful concept of synergy which could be helpful for intermediate learners.

By Pavithra K

Aug 24, 2020

good for beginners, loved the way the instructor explained about synergy (interaction among features)

By Pratham A

Jun 11, 2020

Overall a good project, just a few functions here and there whose use I needed to figure out myself.

By Hariprasad M

Jun 26, 2020

The project explained the basic concepts effectively but it is very short. Otherwise, it's good.

By Sanketh R P

May 16, 2020

Whatever explained is satisfactory ,but it is short.We looking for more big projects.

By Ammar S

Jul 6, 2020

Good analyzing ideas and efficient visualization metrics.

By Yash S

Jun 28, 2020

there was no sound in video no. 6 after minute

By Rohit k

Jun 1, 2020

It is very is easy to understand .

By Chintoo K

Sep 11, 2020



May 14, 2020

Best for beginners

By Deleted A

Apr 16, 2020

Good course

By K S

Jun 16, 2020

just right

By chaitanya d

May 9, 2020

very good

By M M A

Jul 23, 2020