Prefect is a workflow orchestration framework for building resilient data pipelines in Python.
An open-source ML pipeline development platform
Fire up your models with the flame 🔥
A data framework for biology. Makes your data queryable, traceable, reproducible, and FAIR. One API: lakehouse, lineage, feature store, ontologies, LIMS, ELN.
The DBT of ML, as Aligned describes data dependencies in ML systems, and reduce technical data debt
A pipeline to CI/CD of a machine learning model on Google Cloud Run
Find the samples, in the test data, on which your (generative) model makes mistakes.
Efficient streaming data ingestion, transformation & activation
Serving large ml models independently and asynchronously via message queue and kv-storage for communication with other services [EXPERIMENT]
A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.
Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring
This GitHub repository showcases the implementation of a comprehensive end-to-end MLOps pipeline using Amazon SageMaker pipelines to deploy and manage 100x machine learning models. The pipeline covers data pre-processing, model training/re-training, hyperparameter tuning, data quality check,model quality check, model registry, and model deployment.
A complete end-to-end fraud detection system for financial transactions, featuring data pipelines, cost-sensitive ML modeling, explainability with SHAP, threshold optimization, batch scoring, and an interactive Streamlit dashboard. Designed to simulate real-world fintech fraud-risk workflows.
A prefect extension that builds on top of the task decorator to reduce negative engineering!
Repo for running Whylogs as part of a CI workflow using github actions.
Kling AI Python SDK - Production-ready, type-safe Python client for Kling AI's cutting-edge video generation and media processing APIs. Supports async/await, Pydantic models, and comprehensive error h
Demo usage of Weights & Biases for ML Ops
General-purpose tool for running multiple experiments in parallel using tmux sessions with timing and logging
Standardized computer vision pipeline framework with a chainable API and procedurally defined model architecture
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