Making Your Data Useful for Analysis

Having complete and accurate data is a critical first step to being able to learn from it, but part of the complexity of data science is narrowing down what part of the data is important. In this introductory workshop to Machine Learning you will begin to understand how to narrow down the feature scope of your data so that the predictions are based on causation and not just correlation.

You do not need any prior experience with data science to attend this workshop. You are likely someone who is interested in data science, and has 1-2 years coding in Python, or another programming language and feel comfortable enough with Python to be able to code in it during the workshop. You are interested in learning about how to prepare your data for advanced machine learning models using Python and specific Python libraries.

- You should bring your own laptop (Windows or Mac) with an Internet browser.
- You will be using Azure Notebooks, a cloud-based Jupyter Notebooks instance. All you will need is a Microsoft Account, which only requires an email address and for which you can sign up for at the event.

Agenda:
10:00am - 11:00am - Prepping Data for Learning
11:00am - 12:00pm - Principal Component Analysis
12:00pm - 1:00pm - Lunch
1:00pm - 2:00pm - Machine Learning Accuracy
2:00pm - 2:15pm - Break
2:15pm - 3:45pm - Machine Learning Capstone Project
3:45pm - 4:00pm - Wrap Up