In this tutorial you will learn to implement a real time 'A-Z and 0-9 Handwritten Character Recognition Crop Tool' using Python and related modules such as Tensorflow, Keras, OpenCV and Numpy. This tutorial has covered with 3 main sections such as Data Pre-processing, CNN Architecture and Real Time Application Implementation. In data pre-processing we are going to merge two datasets, which consist of both A-Z handwritten characters and 0-9 handwritten digits respectively. Then the individual merged dataset is going to be fed in to our CNN and we are going to pick the best model which will be created at the end of our model training phase. Then we are going to embed our trained CNN model to real time character cropping application and go through with interesting results. Chapters/Sections ================= 00:01:52 - Data Pre-processing 00:27:00 - CNN Architecture 00:40:00 - Real Time Crop Tool Application Download the project ================== Github: https://github.com/Sinsank/A-Z-0-9-Handwritten-Character-Recognition-Crop-Tool.git Google Drive: https://drive.google.com/drive/folders/1LegYVYGUOQwB1pKj5OlvIpDJjG8FD2Ut?usp=sharing References ========== Kaggle A-Z handwritten dataset: https://www.kaggle.com/sachinpatel21/az-handwritten-alphabets-in-csv-format MNIST dataset: http://yann.lecun.com/exdb/mnist/ Social Media =========== Facebook: https://www.facebook.com/SintaX.tech.blog Linkedin: https://www.linkedin.com/in/sineth-sankalpa-9aa4331ab Subscribe 'The Sineth' and hit on the bell icon. https://www.youtube.com/channel/UCQCrO7qrs5f5I13sTZMedag Thanks for watching ❤