Malicious Activity Detection System. Final Year Project. Deep Learning-based solution, which analyses Network Activity sequences to classify whether the certain node is Malicious or Benign. Devising a tool/software which will detect malicious Network Activity Detection using Deep Learning Model. Tools: Python, Neural Network (BERT), Google Colaboratory, PyTorch, Kaggle, Tensorflow, and Flowmeter,

Graph database optimized for fast analysis and real-time data processing. It is provided as an extension to PostgreSQL.

Python sample codes for robotics algorithms.

makes it easy to build, deploy, and manage software robots that emulate humans actions interacting with digital systems and software like manual data entry, manual email boarding , invoice processing

NLP Usage on Quran

Performed Medical Image Segmentation Using (UNet, DoubleUnet and ResUnetplusplus)

bioinformatics combines biology, computer science, information engineering, mathematics and statistics to analyze and interpret biological data.

An app for discovering and sharing places and users can flag their favourite places, and filter the list to show just their favourites

Advanced concept of Swift and C