Packaged version of ultralytics/yolov5 + many extra features
YAPT 2026: Modern PyTorch Training Framework for Faster Deep Learning Workflows
Automated question generation and question answering from Turkish texts using text-to-text transformers
Sales Conversion Optimization MLOps: Boost revenue with AI-powered insights. Features H2O AutoML, ZenML pipelines, Neptune.ai tracking, data validation, drift analysis, CI/CD, Streamlit app, Docker, and GitHub Actions. Includes e-mail alerts, Discord/Slack integration, and SHAP interpretability. Streamline ML workflow and enhance sales performance.
This is a demo project to compare two web scrapping frameworks, Playwright and Selenium and using the new Pipelining tool Dagster
pip install the deep learning & HPC starter pack to begin your project.
This initiative leverages cutting-edge machine learning technique such as Mask R-CNN to automate the identification of buildings in satellite images after disasters. Employing high-resolution Maxar imagery, our models efficiently and accurately pinpoint affected structures, enhancing the speed and effectiveness of emergency responses.
Experiment tracking and model registry in the time series forecasting project
Python package customizing nested cross validation for tabular data.
Experiment tracking and model registry in the images segmentation project
Source code for project with tour-tf-keras.
Example project with scikit-learn and neptune.
Example project with PyTorch and Neptune.
Machine Learning Operations (MLOps) pipeline for my stock prediction forecast model
Tabular data experiment tracking with Neptune
Project with tabular data versioned with Artifacts.
Tests worth running to confirm successful setup & performance of a self-hosted neptune instance.
translating from English to French
To associate your repository with the neptune-ai topic, visit your repo's landing page and select "manage topics."