model-tracking

There are 0 repository under model-tracking topic.

mansha99 / django-model-tracking
How to track model changes in Django and execute dependent workflows
django signals django-model-utils model-tracking
Language:Python 2
crate / mlflow-cratedb
MLflow adapter for CrateDB.
cratedb cratedb-connector mlflow mlflow-compatible cratedb-client cratedb-cloud machine-learning machine-learning-training ml-models ml-training mlflow-server mlflow-tracking model-tracking model-training cratedb-integration mlflow-storage
Language:Python 1
Md-Emon-Hasan / MLFlow-Basic
Covers essential features like model tracking, versioning, and experiment, providing a foundation for efficient ML project lifecycle management.
experiment-tracking mlflow mlfq mlops model-lifecycle model-tracking model-versioning
Language:Python 1
Md-Emon-Hasan / MLFlow-Basic-2.0
Framework for managing machine learning models using MLFlow, focusing on advanced model tracking, versioning, and experiment management.
machine-learning-workflow mlflow mlflow-tracking mlops model-integration model-management model-tracking
Language:Jupyter Notebook 1
gadirajus13 / LifeSavAR
LifeSavAR transforms your smartphone and HoloLens into a lifesaving tool, offering immediate, augmented reality-guided CPR and AED instructions in emergencies. It's your pocket-sized first responder, empowering you to act confidently and effectively when every second counts.
augmented-reality hand-tracking healthcare-application model-tracking mrtk3
Language:ShaderLab 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.
data-preprocessing deep-learning dimensionality-reduction evaluation-metrics feature-engineering kaggle-competition machine-learning-algorithms model-tracking performance-visualization
Language:Jupyter Notebook
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.
ci-cd-pipeline deployment jenkins mlops model-tracking pipeline random-forest-classifier versioning
Language:Jupyter Notebook

model-tracking

mansha99 / django-model-tracking

crate / mlflow-cratedb

Md-Emon-Hasan / MLFlow-Basic

Md-Emon-Hasan / MLFlow-Basic-2.0

gadirajus13 / LifeSavAR

Abdelrahman-Elshahed / Microsoft_Maleware_Prediction_Kaggle_Competition

uddithmachiraju / jenkins-ml-pipeline