GitHub topics: model-tracking
crate/mlflow-cratedb
MLflow adapter for CrateDB.
Language: Python - Size: 236 KB - Last synced at: about 1 month ago - Pushed at: about 1 month ago - Stars: 1 - Forks: 1
uddithmachiraju/jenkins-ml-pipeline
This project automates the end-to-end machine learning training pipeline using Jenkins, ensuring seamless integration and automation. When new data arrives or code is updated, the pipeline automatically preprocesses the data, trains a machine learning model, evaluates its performance, saves the model with versioning, and logs the entire workflow.
Language: Jupyter Notebook - Size: 275 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 0 - Forks: 0
Abdelrahman-Elshahed/Microsoft_Maleware_Prediction_Kaggle_Competition
Malware Detection System using various machine learning and deep learning models, incorporating data preprocessing, feature engineering, and model evaluation techniques, while tracking experiments with MLflow for performance comparison and reproducibility.
Language: Jupyter Notebook - Size: 7.54 MB - Last synced at: 3 months ago - Pushed at: 3 months ago - Stars: 0 - Forks: 0
Md-Emon-Hasan/MLFlow-Basic
Covers essential features like model tracking, versioning, and experiment, providing a foundation for efficient ML project lifecycle management.
Language: Python - Size: 6.18 MB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0
Md-Emon-Hasan/MLFlow-Basic-2.0
Framework for managing machine learning models using MLFlow, focusing on advanced model tracking, versioning, and experiment management.
Language: Jupyter Notebook - Size: 80.1 KB - Last synced at: about 2 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 0
mansha99/django-model-tracking
How to track model changes in Django and execute dependent workflows
Language: Python - Size: 24.4 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
