This program applies a convolutional neural network to vector representations of short DNA sequences. Using the Triplet network [Hoffer & Ailon, 2014], the program learns to embed DNA sequences from the same genome close together in a vector space while maximizing distance to embedded sequences from other genomes. The goal of this project is to explore a novel method for classifying the taxonomy of metagenomic reads.