Model Creation in Azure AutoML and Ingestion Through Excel

Through this talk I will introduce the concept of Machine Learning and frame it in a simple manner to allow comprehension of the base concept. I will also talk about Machine Learning being in fact a branch of Artificial Intelligence and thus should not be thought of as one and the same but similar and distinct of each other. Following this I will then discuss AutoML as a concept paying particular attention to what we are automating (we will show this through talking holistically about the machine learning model lifecycle and highlight what is automated), why it is useful for both novices and experienced users alike (but for different reasons) and what problems can be solved via Azure based AutoML in particular (this will be accompanied with spoken examples to cement what is possible). The meat and bones of the talk will be 3 demos spread through the talk. The first will give a tour of the Azure Machine Learning Studio. The second will go through the process of creating an AutoML model through the Azure Machine Learning Studio from data ingestion to model deployment via a web service. I will also briefly go through a coded example in VS code (with Azure ML extension) showing how the same can be done in a faster and more efficient way if you have the necessary coding knowledge. Finally, the third demo will go through how to get predictions from the deployed model which I will demonstrate using a simple VBA in Excel based interface as excel is something that arguably everyone will be familiar with and so will be a great starting point.