Machine Learning Researcher who delivers ML & AI solutions for data-driven projects in research and business. Especially interested and advanced in building and explaining complex ML/AI models, data inference and creative visualization. Passion for working with others.

Currently working on XAI explanations of CNN Computer Vision Deep Learning classification model detecting COVID-19 disease on lung X-ray images. Below you can find the sample images explaining the pixel importance. Here you can find the research paper and notebook with code.

• Building Vision Transformer (ViT) from Scratch with PyTorch - replication of An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale (Dosovitskiy et al., 2020) research paper

• Explainable AI - Explanation of XGBoost & SVM models of Brain Stroke disease prediction

• Generative Adversarial Networks (GANs)

• Segment Anything Model (SAM) by Meta AI on Medical Images

• Computer Vision Classification Model and XAI Explanations with PyTorch
• Computer Vision Classification Model from Scratch with PyTorch

• Time-series predictions with LSTM Model in PyTorch

• Multiclass Neural Network Classification Model from Scratch with PyTorch

• Binary Neural Network Classification Model from Scratch with PyTorch
• Linear Regression Model from Scratch with PyTorch

• Advanced Visualisation

• Sentiment Analysis & Topic Modeling
• Clustering & Topic Modeling