Handwritten character recognition is an ongoing research field that features machine learning, computer vision and pattern recognition. To do this, one scans a handwritten document and converts it into a simple text document. The basic Optical Character Recognition (OCR) process is to examine the text of a document and convert it into codes used for data processing. In this machine learning project, deep learning techniques were used to model a neural network that recognizes individual handwritten characters and handwritten numerals. To recognize them, a convolutional neural network (CNN) was built to train on alphabets and the digits datasets and further the predictions done by the trained model were visualized using OpenCV.