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GitHub topics: model-tracking

kaymungai/AI-Research-Radar

Automate the tracking, downloading, and analysis of AI papers from HuggingFace. Stay updated with cutting-edge research effortlessly! 🐙📄

Language: Python - Size: 32.2 KB - Last synced at: about 8 hours ago - Pushed at: about 10 hours ago - Stars: 1 - Forks: 0

crate/mlflow-cratedb

MLflow adapter for CrateDB.

Language: Python - Size: 240 KB - Last synced at: 2 months ago - Pushed at: 2 months 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: 580 KB - Last synced at: 3 months ago - Pushed at: 6 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: 7 months ago - Pushed at: 7 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: 6 months ago - Pushed at: 12 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: 2 months ago - Pushed at: 12 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: about 2 years ago - Pushed at: about 2 years ago - Stars: 0 - Forks: 0

Related Keywords
model-tracking 7 mlops 3 mlflow 3 mlflow-tracking 2 machine-learning 2 ai-newsletter 1 pipeline 1 random-forest-classifier 1 versioning 1 data-preprocessing 1 deep-learning 1 dimensionality-reduction 1 evaluation-metrics 1 feature-engineering 1 kaggle-competition 1 machine-learning-algorithms 1 performance-visualization 1 experiment-tracking 1 mlfq 1 model-lifecycle 1 model-versioning 1 machine-learning-workflow 1 model-integration 1 model-management 1 django 1 django-model-utils 1 signals 1 ai-research 1 chinese-summary 1 huggingface 1 large-language-models 1 nlp 1 paper-digest 1 research-tool 1 cratedb 1 cratedb-client 1 cratedb-cloud 1 cratedb-connector 1 cratedb-integration 1 machine-learning-training 1 ml-models 1 ml-training 1 mlflow-compatible 1 mlflow-server 1 mlflow-storage 1 model-training 1 ci-cd-pipeline 1 deployment 1 jenkins 1