Barry Stahl
Barry (he/him) is a .NET Software Engineer who has been creating enterprise solutions for more than 30 years. Barry is also an Election Integrity Activist, baseball and hockey fan, husband of one genius and father of another, and a 30+ year resident of Phoenix Arizona USA. Barry spends his days as a Solution Architect for Carvana and his nights thinking about the next AZGiveCamp where software developers come together to build websites and apps for some great non-profit organizations.
Proposals - Montreal 2024
Defining the Business Domain Using Event Storming
Event Storming models a business domain from the experts' viewpoint. It aids in understanding a domain, defining system components and interactions, discovering unknowns and pinpointing risky areas. Both business experts and engineers love the artifacts it produces. In this session, we'll delve into the process, define its goals and outputs, and walk-through an example to prepare you to bring this important process home to your organization.
Building AI Solutions with Google OR-Tools
In this developer-focused talk, we learn to handle complex problems that have multiple solutions with AI systems. Using the open-source Google OR-Tools, we build c# applications that solve these challenges with mathematical optimization techniques. The session emphasizes practical coding over theoretical mathematics, assisting developers in solving problems such as optimizing routes and creating activity schedules.
Genetic Algorithms
Genetic algorithms "learn" to make better decisions by making continuous improvements in strategy based on Darwinian evolution, using random variations in methodology to improve their fitness. In this talk we walk through an example of creating a genetic algorithm to learn the best strategy for playing a board game. We'll define the DNA of the game and look at what parameters control how the solution evolves and improves.
Amazing Algorithms for Solving Problems in Software
Explore bio-inspired algorithms like Firefly and Ant Colony optimization. In this talk we'll delve into the application of these and other algorithms devised by nature herself, analyzing their pros and cons, and optimal usage. Well also see the power of these algorithms by using one to train a machine-learning model. You'll leave with the tools you need to implement these algorithms in your preferred language.
GPT Embeddings - Not Magic, Just Math
Unraveling the mystery of embeddings from Large Language Models, this talk explores their mathematical foundations and applications. It goes beyond chat and analytics, demonstrating their operational use in C#. Tools like Cosine similarity and clustering are used for comparison. This talk is ideal for developers, but also valuable for data scientists, and those curious about the math behind machine learning and natural language processing.
Montreal 2024 sponsored by
