This document discusses a system for handwritten text recognition using machine learning. It proposes using both convolutional neural networks (CNNs) and recurrent neural networks (RNNs) to recognize handwritten text. CNNs are used for feature extraction from images while RNNs model the sequential nature of handwriting. The system collects data, preprocesses it, trains a model using CNNs and RNNs, and then uses the model to generate recognized text output with high accuracy. Potential applications of this handwritten text recognition system include document digitization, banking, education, and more.