Neuropod is a library that provides a uniform interface to run deep learning models from multiple frameworks in C++ and Python.

Neuropod makes it easy for researchers to build models in a framework of their choosing while also simplifying productionization of these models.

Jon Wood shows the importance of model explainability and a few ways you can do this ML.NET with linear regression models in this video.

Related links:

Paper mentioned in video and where wolf vs husky photo is from – https://arxiv.org/pdf/1602.04938.pdf

Code – https://github.com/jwood803/MLNetExamples/blob/master/MLNetExamples/ModelExplainability/Program.cs

ML.NET Playlist – https://www.youtube.com/watch?v=8gVhJKszzzI&list=PLl_upHIj19Zy3o09oICOutbNfXj332czx

.NET for Apache Spark empowers developers with .NET experience or code bases to participate in the world of big data analytics.

In this episode, Brigit Murtaugh joins Rich to show us how to start processing data with .NET for Apache Spark.

Time index:

  • [01:01] – What is Apache Spark?
  • [02:33] – What are customers using Apache Spark for?
  • [03:50] – What did we create .NET for Apache Spark?
  • [06:30] – Exploring GitHub data
  • [15:012] – Considering data processing in the real world
  • [18:26] – Analyzing continuous data streams

Useful Links

In this video, learn how to consume a GraphQL endpoint from a C# client, specifically an iOS + Android written in C# using Xamarin.

Learn more: https://codetraveler.io/DotNetGraphQL

  • [02:17] – Querying a GraphQL endpoint
  • [06:59] – Viewing the results in a Xamarin app
  • [09:58] – Alternative programming models
  • [11:00] – Follow up resources

Useful Links