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ML.NET is an open-source, cross-platform machine learning framework for .NET developers. It enables integrating machine learning into your .NET apps without requiring you to leave the .NET ecosystem or even have a background in ML or data science. ML.NET provides tooling (Model Builder UI in Visual Studio and the cross platform ML.NET CLI) that automatically trains custom machine learning models for you based on your scenario and data.

Sr. Application Development Manager / Customer Engineer and PhD, David Da-Teh Huang, provides an introduction to supervised machine learning Author Introduction: Dr. Huang obtained his PhD from Caltech in 1990 and has been with Microsoft for over 20 years. He is a Certified Azure DevOps Expert,

Jij Inc. and Toyota Tsusho are working together to begin tackling mobility and traffic challenges using quantum-inspired optimization in Azure Quantum.

Posts and writings by Joel Grus

Featuring 3Blue1Brown Watch the 2nd video on 3Blue1Brown here: https://www.youtube.com/watch?v=MzRCDLre1b4 Support MinutePhysics on Patreon! http://www.patre...

Key element of LSTM is the ability to work with sequences and its gating mechanism.

In this Python Tutorial we build a simple chatbot using PyTorch and Deep Learning. I will also provide an introduction to some basic Natural Language Process...

Ближайшая конференция — DotNext 2020 Piter 15-18 июня, Online Подробности и билеты: https://bit.ly/dotnext2020piter .Need to incorporate ML and AI into your ...

ML.NET is a cross-platform, machine learning framework for .NET developers. Model Builder is the UI tooling in Visual Studio that uses Automated Machine Learning (AutoML) to train and consume custom ML.NET models in your .NET apps. You can use ML.NET and Model Builder to create custom machine learning models without having prior machine learning experience and without leaving the .NET ecosystem.

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