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River is a Python library for online machine learning. It aims to be the most user-friendly library for doing machine learning on streaming data. River is the result of a merger between creme and scikit-multiflow.
Deep learning PyTorch library for time series forecasting
...Currently, Task-TS from CoronaWhy primarily maintains this repository. Pull requests are welcome. Historically, this repository provided open-source benchmarks and codes for flash flood and river flow forecasting. Full transformer (SimpleTransformer in model_dict): The full original transformer with all 8 encoder and decoder blocks. Requires passing the target in at inference.
Froggix is a clone of the classic arcade game Frogger. The aim is to gain points by getting frogs safely across a busy road and a treacherous river to their homes.
lylina is a river-of-news style web-based RSS/Atom feed aggregator loosely based on it's predicessor, lilina. It features a dynamic multi-user system and a scalable database backend, providing the best way to get all your news in one place.
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An assortment of random programs created by a group of internet hooligans known as the Lard Pirates, usually with the intent of being enjoyable for gaming purposes. Currently includes the Flapjack Engine, a River City Ransom clone.
The NHD Software Project is a collection of the utilities, scripts, APIs, standards, and application extensions used for the quality assurance of stream and river data, conflation/generalisation of hydrographic data, and other hydrologic data maintenance.
Project: Dark River Introduction: Dark River is a single player Immersive RPG With RTS Elements. It will be fantasy based and will take place on the world of Antresnia. The world of Antresnia is a vast and beautiful world in the Xeppinia Star System.
An old-shool web-based news reader and bookmarking app
This project intends to provide a free (as in freedom) alternative to web news readers and bookmarking apps.
It is built around the following analogies:
1. You contemplate the river of news flowing down from your selection of sources.
2. You can then use a sieve to filter out and collect the most interesting links.
A demo is at http://wateronmars-demo.herokuapp.com
For the curious developers the aim is also to provide the base mechanics for news and bookmarks manipulations. For instance, there is now a "good enough" database scheme, a RESTful API and a "not too ridiculous" UX.
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