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Avis et commentaires pour d'étudiants pour Multiple Linear Regression with scikit-learn par Rhyme

4.3
étoiles
95 évaluations
16 avis

À propos du cours

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....
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1 - 16 sur 16 Avis pour Multiple Linear Regression with scikit-learn

par Roland N L

Nov 12, 2019

It helps a lot that the programming assignment (= the functions and methods of the various Python libraries for data analysis) is demonstrated in real-time. Thus, one can learn or try to memorize the correct syntax without the need to spend a lot of time to figure out where one forgot a dot, parentheses, square brackets, or an underscore; and focus more on the theoretical model (in this case multiple linear regression) and its related concepts themselves.

par Mayank S

Apr 29, 2020

Good Course. Extended my knowledge to implement multivariable Linear Regression. Thanks.

par Zahid Y

May 23, 2020

Best Course to linear regression basic to get advanced knowledge in neural network

par Diego R G

Mar 31, 2020

Better than the Michigan data science curses by 1 billion miles!

par mdasif r e

May 01, 2020

NICE GUIDED PROJECT BUT TOO SHORT

par MALKAREDDY K R

May 05, 2020

Very informative vedios

par MD Z A

May 02, 2020

#Awesome

par Pulluri R

May 06, 2020

Superb

par 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).

par NHM H I C

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.

par PATLOLLA S R

May 16, 2020

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

par SHRUTI S

May 14, 2020

Best for beginners

par Alan B

Apr 16, 2020

Good course

par Chaitanya r d

May 09, 2020

very good

par ANIL V

May 02, 2020

The initiative by coursera is good. But the instructor made so many mistakes and typos, seems like he is not serious about his work.

par Surineni s

May 12, 2020

ITS GOOD