Implemented Hangman challenge using Trexquant API with 55% accuracy

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Hangman challenge by trexquant is a challenge to predict word, letter by letter.

Solves Hangman using nltk libraries inspired by Trexquant's Hangman Challenge

hangman challenge for trexquant

This challenge is presented by Trexquant as a qualifier for advancing to the next round of interviews for the Global Alpha Researcher position.

Attempting several attacks to getting 60% accuracy on Hangman Challenge TrexQuant

My submission for the Trexquant hangman challenge

Hangman challenge for Trexquant GAR round 1

TrexQuant Hangman Challenge

This repository contains my solution for the Trexquant Hangman Challenge, part of the selection process for the Global Alpha Researcher role. I developed a Transformer-based deep learning agent that achieved a 63.2% success rate on the hidden test set , significantly outperforming the 18% baseline.

Code to play the trexquant hangman challenge

Trexquant Hangman challenge with 58% accuracy

This is my submission for the Global Alpha Researcher (GAR) Program

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It is a solution that I came up with an accuracy of 57% using python.

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Implemented Hangman challenge using Trexquant API with accuracy >50%

Implemented the Trexquant Challenge of playing the Hangman Game