Data Science Center of Excellence Tech Talks

Have you ever wondered what exactly is Data Science? Data Science expands into the world of Machine Learning, Python, Data Processing and more. With the Data Science Center of Excellence, CollabraSpace hopes to bring our expertise and knowledge to everyone wanting to learn more about the ins and outs of data science. Through our tech talks, we hope you gain the knowledge you seek with our presenter Victor Allen.

Recent Tech Talks

March 6th | Churn Prediction with Machine Learning


Join CollabraSpace on March 6th at 3:00PM for a Tech Talk on Machine Learning: Churn Prediction presented by CollabraSpace team member Victor Allen.

Not sure what Churn Prediction is? Come learn with us! Churn Prediction is a common use case in the machine learning domain. Churn, in the data science world, means “leaving the company”. This prediction model helps businesses take actions to prevent customers from leaving a company. Join us as Victor Allen gives insight on how you use churn prediction with machine learning and interesting data sets it provides. 

Watch Talk Here!

Watch Past Tech Talks

Miss a past tech talk? Look no further! All previous talks given by Victor Allen will be available here for your viewing. 

Data Science 101 Tech Talk

The overarching goal of this tech talk is to familiarize you with basic data science skills, roles and responsibilities. This will include techniques and their applications, as well as general questions related to analyzing and handling large data sets. The emphasis of this talk will be on data science applications with a broad explanation of underlying principles.

Machine Learning Tech Talk

The overarching goal of this talk is to familiarize attendees with basic machine learning algorithms and techniques, and their applications. Additional discussion will focus on general questions related to analyzing and handling large data sets and a broad explanation of underlying machine learning principals.

Machine Learning: Classification

In this class you will become familiar with classification model terminologies different types of classifiers and applicability to real world problems. After this lecture students will have access to a Jupyter Notebook, a real-world dataset, and step-by-step instructions to solve a machine learning classification problem. Students will focus on using best practices for classification, including train and test splits, and handling balanced data sets.

CollabraSpace Data Science Center of Excellence Resources



Coming soon!