Project that uses AWS SageMaker to train a neural network and serve the model
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Updated
Mar 29, 2020 - Jupyter Notebook
Project that uses AWS SageMaker to train a neural network and serve the model
Data Science Experiments Repository of Ideas2IT
Raccogliamo qui tutti i link alle risorse menzionate durante i nostri QShare
A ready to use architecture for processing data and performing machine learning in Azure
Sample Airflow ML Pipelines
Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
A simple Python example of a Model Service that can be fronted by the Model Sidecar
Repo for running Whylogs as part of a CI workflow using github actions.
Demo usage of Weights & Biases for ML Ops
Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
A Collection of GitHub Actions That Facilitate MLOps
ORBIT SMKN 4 Bandung team repository for Turnamen Sains Data Nasional 2022 coordinated by Cybertrend Data Academy and Asosiasi Data Sains dan AI Indonesia with supported by several government agencies and universities in Indonesia.
interactive coding environment for microservices demo
Azure Databricks MLOps sample for Python based source code using MLflow without using MLflow Project.
A pipeline to CI/CD of a machine learning model on Google Cloud Run
Efficient streaming data ingestion, transformation & activation
Vehicle data classification (supervised, unsupervised learning)
A prefect extension that builds on top of the task decorator to reduce negative engineering!
Slides of my talk "Is Your ML Model Trustworthy?" at the MLOps World Conference on the 16th of June 2021.
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