In this talk I will present a Neural Network based Handwritten Text Recognition (HTR) model architecture that can be trained to recognize full pages of handwritten or printed text without segmentation of images into lines or paragraphs (as prior art requires). I will talk about the challenges in addressing this problem, review the field, and provide details about our new state of art full page text recognition model. The model is also very easy to replicate using off the shelf modules, and therefore should be of particular interest to ML engineers wanting to develop a state-of-art handwriting recognition system.