With increasing focus on Machine Learning systems in almost every business it is important, to build a great pipeline to train, test and deploy your models. In this session we will show a way to do that with Jupyter Notebooks and Azure

With increasing focus on Machine Learning systems in almost every business area, it is important to build a great pipeline to train, test and deploy your models. In this session we will show a way to do that with Jupyter Notebooks and Azure. The session will cover topics from the creation a CNN in Pytorch to automatically training the model on different machines and using the produced model in ONNX format to make predictions on new data through a web API.

Daniel Heinze

Affiliation: Microsoft

Daniel is a Data Engineer at Microsoft, working with customers to create services that get insights from data and take that to improve the system through Machine Learning.