Cesar de la Torre

Principal Program Manager at the Azure team.

Using ML.NET in Jupyter notebooks

(image) 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-...

Training Image Classification/Recognition models based on Deep Learning & Transfer Learning with ML.NET

(image)         (image)        (image) 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', '...

Run with ML.NET C# code a TensorFlow model exported from Azure Cognitive Services Custom Vision

(image) 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...

What is ML.NET 1.0 – Machine Learning for .NET

(image) 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...