Smart labeling classification datasets mixing ML with deep learning || IoT Virtual Conference

Supervised learning relies on labeled datasets. Since most data are not labeled, the labeling process is very painful, especially when it's done by humans. Why not use computer vision to delegate this burden? The solutions you can find on the market are for labeling image datasets, but I couldn't find labeling numerical datasets that are typical for machine learning. This solution will mix together the power of machine learning multiclassification with the power of transfer learning (by image classification). In this talk, I will demo how I have used Microsoft ML.NET image classification to label data from an IoT device (Raspberry Pi) running .NET 5 on Linux. About Speaker: Daniel Costea is a senior software developer with over 15 years of experience and has been a fan of C # since its inception (2001). Daniel is an active international speaker in the field of .NET technologies at over 40 conferences in the EU and the USA in the last 4 years. Organizer and co-owner of the ApexVox conference. The organizer of community meetings and workshops. Trainer with over 1200 hours of training in .NET web technologies for more than 700 students. Recently Daniel is the author of a series of articles about .NET technologies and in 2019 he became Microsoft MVP on developer technologies. Conference Website: https://www.2020twenty.net/iot-virtual-conference/ C# Corner - Community of Software and Data Developers https://www.c-sharpcorner.com​​ #ml.net #IoT #azureiot #conference #csharpcorner