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MLRun is an open source MLOps platform for quickly building and managing continuous ML applications across their lifecycle. MLRun integrates into your development and CI/CD environment and automates the delivery of production data, ML pipelines, and online applications.
This Guidance demonstrates how to deploy a machine learning inference architecture on Amazon Elastic Kubernetes Service (Amazon EKS). It addresses the basic implementation requirements as well as ways you can pack thousands of unique PyTorch deep learning (DL) models into a scalable architecture and evaluate performance at scale
VirtuTA is an AI teaching assistant that delivers quick, accurate responses to student queries directly on Piazza. Powered by agentic workflows, Google Gemini, and Langchain, it automates both conceptual and logistical course queries.
This repository houses machine learning models and pipelines for predicting various diseases, coupled with an integration with a Large Language Model for Diet and Food Recommendation. Each disease prediction task has its dedicated directory structure to maintain organization and modularity.
The goal of this project is Build and Tune the hyperparameters of a Sklearn model to predict the target using AWS SageMaker, Deploy the model as a Serverless Inference Endpoint and test it Run Batch Transform on the entire input dataset.