usg-artificial-intelligence
There are 3 repositories under usg-artificial-intelligence topic.
- Language:Python 204
nasa / ML-airport-taxi-out
The ML-airport-taxi-out software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for four distinct use cases: 1) unimpeded AMA taxi out, 2) unimpeded ramp taxi out, 3) impeded AMA taxi out, and 4) impeded ramp taxi out. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
Language:Python 36Markov Decision Process (MDP) Toolbox for Python
Language:Python 32The ML-airport-configuration software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for predicting airport configuration as a time series. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
Language:Python 26Contains code for the API that takes in text and predicts concepts & keywords from a list of standardized NASA keywords. API is for exposing models created with the repository `concept-tagging-training`.
Language:Python 19Contains code for training NLP models that takes in text and predicts concepts & keywords from a list of standardized NASA keywords. Code for the API that uses models trained by this repo is in `concept-tagging-api` repository.
Language:Python 18CDCgov / NLPWorkbench
Natural Language processing for Pathology reports on cancer histology, laterality, side, and behavior.
Language:HTML 9- Language:Python 9
Scripts for running several OpenAI Baselines algorithms on all MuJoCo or Roboschool gym environments to compare performance.
Language:Shell 9The ML-airport-arrival-runway software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for predicting arrival runway assignments. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
Language:Python 7The ML-airport-departure-runway software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for predicting departure runway assignments. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
Language:Python 6cdcai / premier_analysis
A deep learning project predicting hyperinflammatory syndrome among COVID-19 patients using EHR data.
Language:Jupyter Notebook 5The ML-airport-taxi-in software is developed to provide a reference implementation to serve as a research example how to train and register Machine Learning (ML) models intended for four distinct use cases: 1) unimpeded AMA taxi in, 2) unimpeded ramp taxi in, 3) impeded AMA taxi in, and 4) impeded ramp taxi in. The software is designed to point to databases which are not provided as part of the software release and thus this software is only intended to serve as an example of best practices. The software is built in python and leverages open-source libraries kedro, scikitlearn, MLFlow, and others. The software provides examples how to build three distinct pipelines for data query and save, data engineering, and data science. These pipelines enable scalable, repeatable, and maintainable development of ML models.
Language:Python 4This repository contains bioinformatics scripts and a Docker container to perform the in silico prediction of Legionella pneumophila serogroup from short read sequences using a supervised machine learning approach.
Language:Shell 3- Language:Python 1
- Language:R 1
Text classification algorithms for autism surveillance
Language:Python 0Classifying multimodal health data with LSTMs
Language:Python 0An ensemble of BERTs for classifying injury narratives
Language:Python 0