2 Explore Logistic Regression

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Содержание

• Event Information
• Content to teach
• Agenda

Event Information

Category	Details
Reactor Topic	Data Science and Machine Learning
Workshop Level	Beginner
Workshop Duration	60 min
Title	Explore Logistic Regression
Description	Logistic regression takes inputs and predicts whether something is true or false. It is usually used for classification of objects by shared qualities or characteristics. In this workshop, we'll look at the loan eligibility process for customers that want to buy a home. After analyzing details provided by customers, we can use logistic regression to determine whether or not they are eligible. To follow along you'll need to have Visual Studio Code installed with the Python extension.
Content	https://github.com/microsoft/Reactors/tree/main/workshop-resources/data-science-and-machine-learning/Data_Science_1/loan-project

Recently Ran: Nov 17 & 18, 2020 - all locations

Here's an overview of what this workshop will cover and suggested agenda to follow with links and resources.

Content to teach

This workshop will take Reactor community members through the Data Science 1 loan project

SHARE THIS LINK WITH REACTOR ATTENDEES: https://aka.ms/DSLoanProject

Agenda

1. Explain the purpose of the workshop 5-10 min
   • Explain the problem that we're trying to solve in the workshop
   • Highlight the variables in the data and what they mean
   • Show the test and train data sets
   • Explain how they can follow along during the workshop
     • Visual Studio Code is needed
     • Python extension is needed
     • Familiarity with Python recommended
     • Encourage attendees to download the data and .ipynb file needed
2. Walk through the notebook 45 min
   • Make sure everyone can get their Jupyter Notebook running in VS Code
   • Go through each section explaining what's happening
   • Encourage questions and answer them as they come in
3. Next steps 2 min
   • Encourage attendees to reference this notebook and go through it on their own time as needed
4. Closing 5 min
   • Q&A
   • Ask attendees to take the survey: https://aka.ms/Reactor/Survey
     • Note: The event code is listed in this issue description and/or your Reactor contact can share that with the community members during the workshop
   • Share Resources
     • Encourage attendees to view other DS and ML workshop materials here: https://github.com/microsoft/Reactors/tree/main/workshop-resources/data-science-and-machine-learning
   • Check if the Reactor contact has other information to share