Azure Machine Learning with Amy Boyd (Cloud Advocate, Microsoft)
The software engineering life cycle is well established in the industry, from requirements, to design, build, deploy and maintain. Now it’s time to apply this to our machine learning projects. Azure Machine Learning is a platform for developing and deploying your machine learning models on Azure. Use your favourite frameworks, libraries and tools to build and deploy your machine learning experiments with the help of the cloud. In this workshop, we will look at the lifecycle of your projects: from data to model and model to consumption in the real world. You can follow along with code samples I will share, as well as using these examples to help you replicate this workshop with your own projects after the event.
This was the first Notts Dev Workshop I had attended at the new Rebel Recruiters offices with a talk demonstrating how to use Azure Machine Learning.
Amy told us how it was possible to apply a software engineering process to machine learning using Azure tools and leverage cloud computing resources.
Following the instructions here https://github.com/amynic/azureml-sdk-fashion we all cloned a copy of the repository and ran the sample code in Azure Notebooks using our own Azure accounts.
I haven’t done much Python previously and no machine learning so it was quite fast paced but interesting to work with something completely different to my normal day job.
The GitHub page also includes the slides from the talk. I haven’t done much AI since my undergraduate degree and it’s pretty amazing how far the technology has moved on in such a short space of time.