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AI-n-DotNet/README.md

AInDotNet

Practical Enterprise AI with Microsoft .NET

I'm a Microsoft AI architect and .NET developer focused on building practical, data-driven AI applications using C#, .NET, ML.NET, Azure AI, Semantic Kernel, and related Microsoft technologies.

Current Focus

  • Predictive AI and forecasting
  • ML.NET
  • Intelligent Document Processing
  • AI assistants and capability-based architecture
  • Enterprise AI architecture
  • Microsoft Azure AI

Featured Projects

ML.NET Taxi Fare Prediction Lab

Hands-on regression exercise demonstrating:

  • Data quality
  • Feature engineering
  • FastTree
  • LightGBM
  • FastForest
  • Model evaluation
  • Error analysis

Resources

Popular repositories Loading

  1. AI-n-DotNet AI-n-DotNet Public

  2. AInDotNet.MLNET.TaxiFare AInDotNet.MLNET.TaxiFare Public

    Hands-on ML.NET regression exercise demonstrating data cleaning, feature engineering, model evaluation, FastTree, LightGBM, and FastForest.

    C#

  3. AInDotNet.MLNET.HousePrices AInDotNet.MLNET.HousePrices Public

    Learn predictive AI with C# and ML.NET by predicting house prices with the Ames Housing dataset. Profile the data, analyze correlations, build a baseline, add numeric and categorical features, comp…

    C#

  4. AInDotNet.MLNET.CustomerChurn AInDotNet.MLNET.CustomerChurn Public

    A C# and ML.NET teaching exercise for predicting customer churn, evaluating classification metrics, tuning thresholds, and connecting predictions to business decisions.

    C#

  5. AInDotNet.MLNET.CreditCardFraud AInDotNet.MLNET.CreditCardFraud Public

    A practical ML.NET lab demonstrating rare-event classification, class imbalance, threshold tuning, business-cost analysis, and fraud decision policies.

    C#