Hi ! I was lucky to have some time during the Virtual ML.Net conference yesterday with the amazing team and attendees. I shared some insights about Anomaly Detection and using drone telemetry as the data source. As usual now it's time to share the resources Slides Source Code Source Code is available here Recording https://youtu.be/ch1aeidOt_M?t=21841
Hi ! April is gone, and also my event-free calendar until May. And I'm super lucky to host a session at the Virtual ML.Net Community Conference The Virtual ML.NET Community Conference is a 2-day community driven conference on all things ML.NET.The conference will be streamed live on Twitch and YouTube.It’s 100% free and open for … Continue reading #Event – Drones 🚁 and Anomaly Detection 📈 at The Virtual ML.NET Community Conference, May 7/8
Hi ! I had a great time early in the day with some my friends from Europe. As usual, time for slides and code: Slides Code https://github.com/elbruno/events/tree/main/2021%2002%2023%20MVP%20Fussion%20MLNet Resources Get started at http://dot.net/mlTry the samples at http://aka.ms/mlnetsamplesRead the docs at http://aka.ms/mlnetdocsRequest features or contribute at http://aka.ms/mlnetGet help for going into production https://aka.ms/mlnetprodML.NET Model Builder, Approachable machine … Continue reading #Event – “ML.Net and AutoML” at the MVP Fusion and Friends 2021 . Session Resources
Hi ! I haven't write a lot about ML.NET Command-Line Interface (CLI) (see references), and that's a shame. It's very powerful and also it supports most of the ML.Net features, like in example: Model Builder Image Classification scenario. The ML.NET CLI automates model generation for .NET developers. To use the ML.NET API by itself, (without … Continue reading #ML.NET Image Classification with ML.NET Command-Line Interface (CLI), no #VS2019 needed !
Hi ! This is a sequel part after yesterday post on the new Model Builder Object Detection scenario. I've found this error, and it took me some time to figure out the reason. As usual, an error on the Model Builder, with very few details and the suggestion to check more details on the Azure … Continue reading #VS2019 – ML.NET Model Builder for Object Detection, be careful with file names and VoTT
Hi ! There is a new scenario available in ML.Net Model Builder for Visual Studio 2019: Object Detection. This scenario is not just image tagging, this scenario allows us to detect objects in an image, and get the specific coordinates and size of the detected objects. As usual, it requires a starting data set with … Continue reading #VS2019 – ML.NET Model Builder for Object Detection using #Azure Compute #mlnet #objectdetection
Hi ! Great session yesterday with Matthew and the Central Ohio .NET Developer's Group (CONDG). And the excuse was to talk about Machine Learning .Net. As usual, now it's time for slides and code Slides Code The code used during the session is available here: https://github.com/elbruno/events/tree/main/2020%2009%2024%20CONDG%20MLNet Session Recording (I'll update this block when the recording … Continue reading #Event – Resources used on “Getting Started with Machine Learning .NET” for the Central Ohio .NET Developer’s Group (@CONDG)
Hi ! I my previous posts on Model Builder, I show the differences between using the CPU and GPU to train a model. There is a 3rd option, which involves an Azure ML Experiment, and performs the training on the cloud. It took me some time, to setup this environment, mostly because I tried to … Continue reading #VS2019 – ML.NET Model Builder training using GPU, CPU and … Azure !
Hi ! I'm back to share some amazing ML.Net Experiences. This time with my friends from [Central Ohio .NET Developer's Group (CONDG)] with a virtual event on [Thursday, September 24, 2020]. It's been a while since my Machine Learning.Net sessions, so I'm creating one from scratch to cover all the amazing new features that we … Continue reading #Event – Getting Started with Machine Learning .NET
Hi ! Yesterday I wrote about the new options that we have to train models in ML.Net Model Builder. The main new is that we have the option to use our GPU to train models. Quick recap, Model Builder supports 3 specific training environments Local (CPU)Local (GPU)Azure Yesterday I tested train a small image recognition … Continue reading #VS2019 – ML.NET Model Builder GPU vs CPU test: 4 times faster !