As a Visual Studio TypeScript and C# developer building web-based, spatial information systems targeting a variety of platforms that leverage ESRI and SQL Server, I want a starter kit so that I can rapidly build implementations.
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As a user, I want a walk through of creating a web app from the `aurelia-axel` starter kit, based of a familiar database (Northwind).
Mailgun integration for Pyramid framework
Fully functional Hungarian Algorithm implementation in Ada
- hungarian-algorithm
- ada
- munkres
- kuhn
Algorand Tools for PowerShell
An expressive high level language for the Algorand block chain that compiles to TEAL code.
- blockchain
- algorand
- teal
- smartcontract
Finds prime numbers using the Sieve of Eratosthenes algorithm.
A library to parse and manipulate an algebraic superset/semantic application of JSON
Web Audio Musical Step Sequencer for music exchange
Python implementation of the goldeneye algorithm to investigate how classifiers utilise the structure of a dataset.
- data-science
- model-explanation
Will output a skeleton of LOAD CSV Cypher script for Neo4j, based on .... a csv file and user hints
MicroPython wpa-supplicant
⛓️ Modern Swift SDK for the Algorand blockchain
🏷️ NFT metadata done right
🌿 Mint NFTs from Swift, because why not
- algorand
- blockchain
- minting
- nft
The repository host gives no description.
Algorand Unity SDK
- sdk
- unity
Dynamic and static bindings to SDL2_gfx, compatible with -betterC, @nogc, and nothrow.
Vector-field consistency model for HBase fine-grained inter-DC replication with Quality-of-Data at CloudCom
Debug Adapter Protocol Debugger for the Algorand Virtual Machine
- algokit
- app
Autonomous AI agent orchestration with on-chain identity, multi-agent councils, and self-improving code -- powered by Algorand
Exploit black-box recommenders for algorithm selection.
Partition (W)ARC Files by MIME Type and Year
- web-archiving
- webarchive
- hadoop
- warc
Comparing the performance of Stacked Ensemble Learning & machine learning algorithms like Random Forest, Decision Tree, Adaboost, Gradient Boost and XGBoost Classifier in Python for Stock Market Trend Prediction.