This repo contains codes for simulating monte calo algorithm for data preprocessing turned to data processing .Most of the codes and simulations are estimation of pi base models.
phase 1 -Simulation of classical monte carlo phase 2 -attempting to optimize classical monte carlo with a different sampling methord phase 3 -optimizing with markov chain and multi markov chain phase 4 -increasing the dimensions to 3D phase 5 -attemting to implement custom problems like weather patterns and alzheimer's phase 6 -implementing the base estimation of with quantum computing algorithms phase 7 -combining mcmc and greedy controlled via simulated annealing for a custom data prioritization algoithm
add a case where greedy can be quantumized by grovers amplitude amplification
Get the algorithm to prioritize the high quality data points based on conditions given or search the dataset for points that match the description potentially lower energy consuming ml algorithms proposed name - YO -(Yukthi opus)