© Zulkarnine, 2022. Algorithm to solve Wordle 100% of the time within 6 attempts. You can go ahead and run main.py to run it for all 2315 Wordle words and it solves 100% of them correctly within 6 attempts.Example output: Ran: 2315 games. Solved: 2315/2315 = 100.00% You can also run solver.py to get a sense of how it’s guessing and what is the Wordle game simulation returning. (I.e. the colored blocks) Example output:

This is the implementation of our paper “Sequential Prediction of Social Media Popularity with Deep Temporal Context Networks“. Dataset To successfully test performance, we created TPIC Dataset, a temporal popularity image collection dataset. Overview Our DTCN contains three main components, from embedding, learning to predicting. With a joint embedding network, we obtain a unified deep representation of multi-modal user-post data in a common embedding space. Then, based on the embedded data sequence over time, temporal context learning attempts to recurrently […]

All algorithms have a complexity known as Big O Notation, the more complex an algorithm, the less efficient it gets as more data is introduced. Listed below are the Big-O complexities listed from best to worst:

This is a demo for AAD algorithm. The subroutine of the anisotropic diffusion algorithm is modified from Mr. Michael Aye’s repository in https://github.com/michaelaye/pymars/blob/ca62a17c682f999c490cc0dbceb01433c385ced0/pymars/anisodiff2D.py.We have provided the code of Asynchronous-Anisotropic-Diffusion-Algorithm, and the Optics Express paper here, please access the data we used refer to https://github.com/BJTUSensor/AD-algorithm/blob/main/data.mat. Operating environment: Python 3.7 GitHub View Github    

GNAT GNAT is NOT Algorithmic Trading! GNAT is a financial tool with two goals in mind: To provide a dashboard with the detailed stock/crypto information of your choice. To provide confidence in the Harvest framework which GNAT heavily relies on. How to use pip install -r requirements.txt python gnat.py -OR- python gnat.py my_config.yaml Input the requested information and then go to localhost:8050 to see the dashboard. How it works On start, GNAT asks the user what assets they want to […]

An algorithm (implemented here in Python) mainly inspired by the Bucket Sort (and the Pigeonhole Sort) and works by placing the values of a given unsorted array into buckets where the number of buckets is equal to the length of the unsorted array. In addition, it recursively runs the sorting algorithm on any buckets that contain more than one element and is unsorted. For more, including why the algorithm has been implemented in this way and how it compares against […]

this repo contains everything i learn about quantum computing and algorithm on quantum computing what is aquantum computing quantum computing is an area of study focused on the development of computer based technologies centered around the principles of quantum theory. quantum computing uses a combination of bits to perform specific computational taks. all at much higher efficiency than their classical counterparts. development of quantum computers mark a leap forward in computing capability, with massive performance gains for specifig use cases. […]