Showing results for 2019 - Cesar de la Torre

Nov 6, 2019
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Using ML.NET in Jupyter notebooks

Cesar De la Torre
Cesar De la Torre

I do believe this is great news for the ML.NET community and .NET in general. You can now run .NET code (C# / F#) in Jupyter notebooks and therefore run ML.NET code in it as well! - Under the covers, this is enabled by 'dotnet-try' and its related .NET kernel for Jupyter (as early previews). The Jupyter Notebook is an open-source web ...

ML.NETMLMachine Learning
Sep 6, 2019
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Training Image Classification/Recognition models based on Deep Learning & Transfer Learning with ML.NET

Cesar De la Torre
Cesar De la Torre

                Blog Post updated targeting ML.NET 1.4 GA (Nov. 2019) Note that this blog post was updated on Nov. 6th 2019 so it covers the updates provided in ML.NET 1.4 GA, such as Image classifier training and inference using GPU and a simplified API. Context and background for 'Image Classification', 'training vs. scoring' and ML....

ML.NETMLMachine Learning
Jun 5, 2019
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Run with ML.NET C# code a TensorFlow model exported from Azure Cognitive Services Custom Vision

Cesar De la Torre
Cesar De la Torre

With ML.NET and related NuGet packages for TensorFlow you can currently do the following: However, in the scenario where you want to train with your own images, the Transfer Learning approach can be a bit complex because even without taking into account the code implementation for transfer learning you'll need to find a base TensorFlow ...

ML.NETMLMachine Learning
May 28, 2019
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ML.NET Model Lifecycle with Azure DevOps CI/CD pipelines

Cesar De la Torre
Cesar De la Torre

As a developer or software architect, you are focused on the application lifecycle – building, maintaining, and continuously updating the end-user business application, as illustrated in the simplified image below: When you infuse AI (such as an ML.NET model) into your application, then your application lifecycle needs to be extended so it ...

MLmlnetmachinelearning
May 6, 2019
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What is ML.NET 1.0 – Machine Learning for .NET

Cesar De la Torre
Cesar De la Torre

Today, coinciding with //BUILD 2019/ conference, we’re thrilled by launching ML.NET 1.0 release! You can read the official ML.NET 1.0 release announcement Blog Post here and get started at the ML.NET site here. In this blog post I'm providing quite a few additional technical details along with my personal vision that you might find ...

ASP.NET Core.NET CoreML.NET
Mar 24, 2019
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How to optimize and run ML.NET models on scalable ASP.NET Core WebAPIs or web apps

Cesar De la Torre
Cesar De la Torre

Context ------ UPDATE on May 13th 2019: The recommended way to deploy/run an ML.NET model into ASP.NET Core web apps or WebAPI services is by using the 'Microsoft.Extensions.ML' Integration package. Read about it in this tutorial: - Deploy an ML.NET model in an ASP.NET Core Web API The tutorial above uses optimized code based on an ....

ASP.NET CoreML.NET