Duration: 2h 49m | .MP4 1280x720, 30 fps(r) | AAC, 48000 Hz, 2ch | 1.45 GB
Level: Intermediate | Genre: eLearning | Language: English
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.

SkillShare - Introduction To Linear and Logistic Regression Machine Learning-SkilledHares
English | Size: 519.64 MB
Category: Machine Learning