PyTorch

Practical tasks on Deep Learning (DL) and Neural Networks (NN). 🤖

AI Radiology Copilot (ARC) is a CNN model app to recognize and label brain tumors in MRI scans.

Using a Residual Neural Network to predict coordinates from a single image from a Google Street View image within the United States

Code repository for GAME-Net (Graph-based Adsorption on Metal Energy-neural Network), a graph neural network for predicting the adsorption energy of closed-shell molecules on metal surfaces.

Advanced Neural Networks

Repository of real applications of neural networks coded in Python with TensorFlow/Keras and PyTorch.

Linear regression refresher

A real-time human counting system with age and gender classification.

Scholara: A Virtual Assistant Powered by LLM, RAG, and AI Agent.

Finding the right scholarship can be a timeconsuming and frustrating process. You'll likely spend hours poring over university websites, communicating with current students, and scouring the internet for information. Unfortunately, even after all that effort, there's no guarantee you'll find the perfect scholarship. That's where our AI scholar comes in. Let us handle the legwork for you, and we'll provide personalized assistance to find the most suitable scholarship for you and answer all your questions about the scholarships that interest you. We solved this by using LLM to provide a human-like when answer the students, RAG we build our own vector database to get more suitable scholarships from it based on student information and desire, also to keep our system up-to-date with all the updated information about the scholarships we built AI Web agent this helps the system to be aware about all the updates in the scholarships information, and new scholarships.

A Python library for Secure and Explainable Machine Learning

Documentation available @ https://secml.gitlab.io

Follow us on Twitter @ https://twitter.com/secml_py

ANTIDOTE's ACTA Module for Finetuning Transformers for Argumentation Mining.

A CBIR and classification system that uses both representation learning and handcrafted features to build the image descriptors.

расширение исходной модели

The project entailed building an image classification model using PyTorch, integrated with Azure ML for data handling, model training, and deployment. Key steps included initializing Azure ML Workspace, processing the dataset, developing the model in PyTorch, and deploying it on Azure for real-world inference. This project showcases the synergy between advanced machine learning frameworks and cloud computing platforms in solving complex image classification tasks.

Population density tracker using Computer Vision.