What happens when you encounter large data sets that are more nuanced than a set of concrete numbers? When you begin to explore natural language or data sets with many potential influential features, you require more complex and predictive machine learning models. In this advanced Data Science workshop, learn about K-Means, Naive Bayes, and Regression models that will better support complex data and questions.
You should have some basic data cleansing, manipulation, and preparation in Python prior to attending 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 apply advanced machine learning models to data that you have prepared. .
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.
About the speaker:
Christopher Harrison has been an educator and trainer for twenty years as an MCT and full-time Microsoft employee. He has developed many MVAs and EdX Courses, as well as conducted countless trainings on every technical topic from SharePoint and ASP.NET to TypeScript, Django, and AI. Christopher is passionate about technology and learning how to integrate new topics into interesting and applicable projects. Most recently, Christopher has moved to leading the efforts around Microsoft’s hackathon strategy, developing workshops and resources for learners to discover how to enhance their hacks with the power of Azure.
09:30 - 10:00 Registration
10:00 - 11:00 K-Means
11:00 - 12:00 Naïve Bayes
12:00 - 13:00 Lunch
13:00 - 14:00 Linear Regression
14:00 - 14:15 Break
14:15 - 15:45 Machine Learning Capstone Project
15:45 - 16:00 Wrap Up