Chess-Position--Chess-Moves

Context The objective of this dataset is to create a chess engine through machine learning. In this first part we will first predict the pieces to be moved depending on the position of the chessboard This is inspired by this research (https://pdfs.semanticscholar.org/28a9/fff7208256de548c273e96487d750137c31d.pdf) but by comparing several approaches and having the best performance The data used by this competition is a processed version of the dataset https://www.kaggle.com/milesh1/35-million-chess-games which Content The players are represented by the winning player and the losing player. The first 64 columns represent the 64 squares of the chessboard and each value corresponds to the piece which is on this square the unique values are as follows WR: Rook of wining player WB: Bishop of wining player WN: Knight of wining player WQ: Queen of wining player WK: King of wining player WP: Pawn of wining player LR : Rook of losing player LB : Bishop of losing player LN : Knight of losing player LQ : Queen of losing player LK : King of losing player LP : Pawn of losing player The next turn is the winner's turn so the output is the algebrical value of the box containing the piece to move A1 to H8 (64 classes)