MachineLearning-BaseballPrediction-BlazorApp and MLDotNet-BaseballClassification
These are ecosystem siblings where the second project (ML.NET classifier training) provides the trained machine learning models that the first project (Blazor web app) consumes and deploys for real-time predictions.
About MachineLearning-BaseballPrediction-BlazorApp
bartczernicki/MachineLearning-BaseballPrediction-BlazorApp
Machine Learning over historical baseball data using latest Microsoft AI & Development technology stack (.Net Core & Blazor)
Implements in-memory ML.NET models with decision thresholding and what-if analysis capabilities, contrasting rules-based and machine intelligence approaches for Hall of Fame prediction. Features agentic AI integration via Semantic Kernel for autonomous research and analysis, with results streamed to Blazor clients using SignalR. Built on .NET 9 with Aspire orchestration and Docker containerization for local or cloud deployment.
About MLDotNet-BaseballClassification
bartczernicki/MLDotNet-BaseballClassification
Machine Learning training job using historical baseball data & ML.NET to build a complete set of classifiers.
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