Facundo Santiago

trunkbased-mlops. This repository showcases how to implement trunk-based development workflow while working in a Machine Learning project.

prometheus. Prometheus is a machine learning powered solution for early detection of fires in national parks

mlflow-deployments. Source code for the post Effortless deployments with MLFlow, showcasing how logging models using MLFLow can provide you want to easily deploy them in production later.

synapse-cicd. A GitHub Actions/Azure DevOps implementation of a CI/CD workflow for Azure Synapse or Azure SQL Database

ContrastiveLearning. This repo demostrates how to use the concept of contrastive learning in an anommaly detection setting with autoencoders (also know as discriminative autoencoders)

mlproject-sample. Sample repository about how to structure an ML project using software engineering practices

azureai-rag-hack. Example about how to use the right model for the right job in a RAG setting

dogs-vs-cats-benchmark. Benchmarking Azure Machine Learning Services for training a model with GPU and PyTorch. Full post at Medium

pnp-databricks-monitoring. This sample shows how to stream Databricks metrics to Azure Monitor (log analytics) workspace

jobtools. Facilitates the use of Python from the command line with automatic params parsing

M72109. Repositorio para el curso M72109

azureml-julia. An example about how to train a tree-based decision model using Julia (1.7.2) for the popular Iris dataset in Azure ML.

azureml-fabric-together. This repo contains two examples about how you can use Azure Machine Learning and Fabric together.

azureml-components. This repository contains un-official Azure Machine Learning components to use in AzureML pipelines.

portable-sparkml. This repository shows how to create containerized versions of models trained with spark MLLib

aml-modules. A repository of drag-and-drop custom modules for Azure Machine Learning Designer

E72102.

aitour2019. Samples shown in Microsoft AI Tour 2019 for sessions "Taking Machine Learning notch to the next level with Databricks" and "Superman vs Batman: Python and R in Azure"

interpret. A repository with examples about how to use different interpretability techniques.

azureai-x-arize. Jupyter Notebook

ghu-pm-buddy. GitHub Universe sample