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we aim to provide a framework for understanding the linguistic and cultural diversity of the Arabic-speaking world and to help scholars and researchers analyze and compare these dialects. So we developed a model that takes a text as an input and gives you the name of the dialect as an output.
This project was my final Bachelor's degree thesis. In it I decided to mix my passion, music, and the syllabus that I liked the most in my degree, deep learning.
This repository holds one of my first Deep Learning projects. The project implements an MNIST classifying fully-connected neural network from scratch (in python) using only NumPy for numeric computations. For further information, please see README.