You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
The repository contains the code and notebooks for the tutorials on how to extract embedding features from pictures using the ResNext model. The quality and effectiveness of the techniques are proved by the clustering in the embedding space and the correlation of clusters with their corresponding labels.
This notebook explores the application of Regex and embedding techniques in Arabic Natural Language Processing (NLP). It covers the use of regular expressions for text parsing tasks and delves into various word embedding methods, including Word2Vec and FastText, for semantic analysis and representation of Arabic text data.