AlphaClaw

Screenshots

Problem Statement

'- A complex NFT price prediction model using autokeras.Based on the previous trades, creator(s), platform sold at, volatility.This model can also used to predict what could be the price of an NFT if you make them and are ready to put it on a platform.So far rarible, cryptokittes and cryptopunks are learnt fully by alphaclaw and many other nft tokens

Solution

'- Using the state of the Art image regression models from SDDs to YOLO to resnets .Tested each model to pick the most accurate model.Used the whole of cryptokitties , cryptopunks and some of rarible as a dataset with their past prices + owner profiling.The app runs on a flask server, the model is a tensorflow model which does the magic.The front-end is vanilla HTML + CSS and a few more beautifying libraries. (because I am solo and didn't have enough time)