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36 lines
1.5 KiB
36 lines
1.5 KiB
# Logistic Regression to Predict Categories
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> Sketchnote on Logistic Regression
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## [Pre-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/11/)
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### Introduction
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In this final lesson on Regression, one of the basic 'classic' ML techniques, we will take a look at Logistic Regression. You would use this technique to discover patterns to predict categories.
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In this lesson, you will learn:
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- A new library for data visualization
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- Techniques for Logistic Regression
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## Prerequisite
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Having worked with the pumpkin data, we are now familiar enough with it to realize that there's one small category that we can work with: Color. Let's build a Logistic Regression model to predict that, given a pumpkin's size, what color it will be (orange or white). There is also a 'striped' category in our dataset but there are few instances, so we will not use it.
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> 🎃 Fun fact, we sometimes call white pumpkins 'ghost' pumpkins. They aren't very easy to carve, so they aren't as popular as the orange ones but they are cool looking!
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### Preparation
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We have loaded up the [starter notebook](./notebook.ipynb) with pumpkin data once again and cleaned it so as to preserve a dataset containing Color and Item Size.
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---
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## 🚀Challenge
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Add a challenge for students to work on collaboratively in class to enhance the project
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Optional: add a screenshot of the completed lesson's UI if appropriate
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## [Post-lecture quiz](https://jolly-sea-0a877260f.azurestaticapps.net/quiz/12/)
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## Review & Self Study
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**Assignment**: [Assignment Name](assignment.md)
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