aistream-peelout Goto Github PK

.github

GitHub for AIStream

awesome_time_series_in_python

This curated list contains python packages for time series analysis

benchmark_forecasting

Notebooks related to benchmarking different models on COVID, River Flow, and Grocery data

experiment_configs

flow-api

Flow Forecast wrapped in an easy to use production API.

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

flow-mts-datalake

Code for our multivariate data-lake

flow_docker

Files needed to run flow-forecast as a container.

flow_tutorials

Public tutorials of using Flow Forecast for forecasting and classifying time series data

outfit-it

Rapidly refactor machine learning model code for production

parl_docker

Up to date Docker container for training ParlAI models.

peelout-core

Peelout is an open source framework that aims to make it easy to refactor, deploy, and monitor deep learning models

pytorch_geometric_temporal

A Temporal Extension Library for PyTorch Geometric

real-time-voice-cloning

Clone a voice in 5 seconds to generate arbitrary speech in real-time

staged-recipes

A place to submit conda recipes before they become fully fledged conda-forge feedstocks

time_series_notebooks

Repo of all

water

Water is an attempt to create an open-access dataset and ML framework for monitoring/forecasting stream flows and snowpack depth.