PyCloud Mini-Conference
This is supporting material (slides, github repo links etc) for the sessions in PyCloud - event URL: konf.me/pycloud
- Learning resources for AzurePyday:
[Links] https://aka.ms/azurepyday
- "Distributed system analysis made easy with PBench", Anisha Swain & Riya, Associate Software Engineer, Red Hat
- "Leveraging Serverless and Cognitive Services for COVID-19 Data Processing", Manoj Ganapathi, Digital Technology Consultant, Cloud and DevOps Specialist
[Slides] https://www.slideshare.net/CodeOps/leveraging-serverless-and-cognitive-services-for-covid19-data-processing [GitHub code] https://github.com/ManojG1978/azure-functions-cognitive-services-covid-sample
- "Building Search Experience for a Python Web Application", Aravind Putrevu, Developer Advocate, Elastic
[Slides] https://aravind.dev/2020/05/elastic-app-search-python/
Exploring Natural Language Processing using Azure, Usha Rengaraju, Principal Data Scientist, Infinite Sum Modelling
[Slides and Code] https://github.com/ushareng/PyCloud
- “Identifying defaulters using Machine Learning", Ritesh Modi, Hon. Microsoft Regional Director
[Slides] https://www.slideshare.net/CodeOps/identifying-defaulters-using-machine-learning-ritesh-modi
The Supporting source jypyter notebook files (are added in this repo itself)
- "Using the Azure Machine Learning Python SDK to Train a PyTorch model at Scale", Henk Boelman, Cloud Advocate at Microsoft
[Slides] https://speakerdeck.com/hnky/build-and-deploy-pytorch-models-with-azure-machine-learning