Packaged version of ultralytics/yolov5 + many extra features
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Updated
Nov 11, 2024 - Python
Packaged version of ultralytics/yolov5 + many extra features
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.
Experiment tracking and model registry in the time series forecasting 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 images segmentation project
Source code for project with tour-tf-keras.
Example project with scikit-learn and neptune.
Example project with PyTorch and Neptune.
Python package customizing nested cross validation for tabular data.
translating from English to French
AAPL Stock Analysis adapted from Author Katherine (Yi) Li using Neptune Labs Neptune.ai
Project with tabular data versioned with Artifacts.
Implement CI/CD pipelines to train and deploy machine learning models using Github Actions
Tabular data experiment tracking with Neptune
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