This Asset we are sharing with you the Machine Learning with Logistic Regression in Excel, R, and Power BI free download links. This is a premium product and you will get it free on here. PSDLY made to help people like graphic designers, video creators, web developers, freelancers, filmmakers, etc. On our website, you will find lots of premium assets free like Free-course/tutorials, Lightroom Preset, PS action, Mockups, Videohive Items, Premium Sounds, Web Templates, and much more.
Free download — Machine Learning with Logistic Regression in Excel, R, and Power BI
Excel, R, and Power BI are applications universally used in data science and across businesses and organizations around the world. If you’ve spent any time trying to figure out how to better model your data to get useful insights from it that you can act upon, you’ve most likely encountered these applications. In this course, Helen Wall shows how to use Excel, R, and Power BI for logistic regression in order to model data to predict the classification labels like detecting fraud or medical trial successes. Helen walks through several examples of logistic regression. She shows how to use Excel to tangibly calculate the regression model, then use R for more intensive calculations and visualizations. She then illustrates how to use Power BI to integrate the capabilities of Excel calculations and R in a scalable, sharable model.
About: Machine Learning with Logistic Regression in Excel, R, and Power BI
File Name: | Machine Learning with Logistic Regression in Excel, R, and Power BI |
Content Source: | https://linkedin.com/learning/machine-learning-with-logistic-regression-in-excel-r-and-power-bi |
Genre / Category: | Programming |
File Size : | 1.5 GB |
Publisher: | |
Updated and Published: | November 06, 2021 |

DOWNLOAD LINK : Machine Learning with Logistic Regression in Excel, R, and Power BI
FILEAXA.COM – is our main file storage service. We host all files there. You can join FILEAXA.COM premium service to get access to our all files with unlimited download speed.