How to Port Desktop Applications to .NET Core 3.0
Explore .NET Core 3.0's enhancements for desktop, cloud, web, IoT, and ML applications. Learn to port desktop apps, use Windows Compatibility Pack, and discover Razor Components and ML.NET.
Machine Learning Crash Course With ML.NET
Comprehensive introduction to machine learning concepts and hands-on demonstration using ML.NET, covering key processes from data loading to model evaluation with practical C# examples.
Microsoft AI: MLNet Framework en C# - Transfer Learning para Clasificación de Imágenes
Integra MLNet con TensorFlow para clasificar imágenes de superficies de cemento mediante transfer learning y la API de ML.NET Image Classification Library.
Microsoft AI: ML.NET Framework in C# - Transfer Learning for Image Classification
Aprende a entrenar modelos de aprendizaje profundo personalizados utilizando transferencia de aprendizaje, TensorFlow y ML.NET para clasificar imágenes de superficies de concreto.
Beyond Sentiment Analysis - Real Time Object Detection with ML NET
Explore real-time object detection using ML.NET, learn about computer vision applications, and discover tools for image labeling and model building in the .NET ecosystem.
Predicting F1 Race Strategies using ML.NET
Explore ML.NET for predicting F1 race strategies. Learn to analyze historical data and make informed predictions about team decisions in upcoming Grand Prix events.
Machine Learning in C# - Introduction to ML.NET
Discover ML.NET: Build machine learning applications using C# and .NET. Learn data preparation, model evaluation, and deployment techniques for integrating ML capabilities into your .NET projects.
Introduction to ML.NET
Explore ML.NET for infusing custom AI into .NET apps. Learn about scenarios, architecture, and hands-on examples like GitHub issue classification and content-based filtering.
How to Use ML.NET to Write Crushing Metal Riffs
Explore deep learning with ML.NET to generate metal riffs. Learn about neural networks, RNNs, and guitar tablatures while discovering how to apply machine learning to music composition.
Introducción a ML.Net SDK: Análisis de Sentimientos en C# - Español
Desarrolla análisis de sentimientos con ML.Net SDK en C#. Aprende a implementar machine learning para procesar y clasificar texto en español.
Beyond Sentiment Analysis - Object Detection with ML NET
Explore object detection using ML.NET Model Builder, overcoming resource limitations. Learn image labeling tools, practical examples, and use cases for efficient computer vision implementation in .NET solutions.
Microsoft ML.NET Framework: Sentiment Analysis Application in C#
Explore sentiment analysis using ML.NET in C#. Learn to develop applications that analyze text sentiment with Microsoft's machine learning framework.
Machine Learning for .NET Developers
Discover how to integrate machine learning into .NET applications using ML.NET and Microsoft tools. Learn ML basics and start applying it to your projects without extensive data science knowledge.
Machine Learning for .NET Developers
Explore machine learning basics and learn to integrate ML.NET into .NET applications, making AI accessible for developers without requiring extensive data science knowledge.
Machine Learning Simplified for Developers with ML.NET
Explore ML.NET for developers: prototype, tweak with data science, and generate code for applications. Learn to create and improve machine learning models using ML.NET Model Builder and basic data science techniques.
Integración de MLNet Framework y TensorFlow en C# para Clasificación de Imágenes
Integra MLNet de Microsoft con TensorFlow para clasificación de imágenes en C#. Aprende a utilizar el modelo ImageNet en aplicaciones prácticas.
Microsoft ML.NET Framework Integration with TensorFlow for Computer Vision Classification
Explore MLNet and TensorFlow integration in C# for CV classification using Imagenet model. Hands-on demo with practical code examples.