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Dimitris Fanis

Classification & Prediction of Handwritten Digits in the Kannada Language

This is a Machine Learning project using Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) with TensorFlow and Keras in order to classify and predict an alternative MNIST digits database, that of the Kannada hand-written digits.

Project Image

Photo by Markus Spiske on Unsplash

Project Overview

This is a Machine Learning project using Deep Neural Networks (DNNs) and Convolutional Neural Networks (CNNs) with TensorFlow and Keras, and more specifically, it is about a classification problem in regard to the recognition and prediction of the Kannada hand-written digits.

The dataset used is an alternative one with reference to the popular MNIST digits database, and the project was constructed in the context of a kaggle class competition (module CS985 Machine Learning) at Strathclyde University (academic year 2019-20).

A range of deep neural network architectures and techniques are applied with the final goal of finding the optimal model for the hand-written digits' predictions.

Tools & Technologies Used

Deep Learning
Convolutional Neural Networks (CNNs)
Classification
Model Evaluation
TensorFlow
Keras