This project aims to convert low resolution images to high resolution images by leveraging the power of Generative Adverserial Networks. This has implementation in areas such as medical imaging, surveillance, and remote sensing.
Conducted EDA and predict customer churn using Artificial Neural Networks (ANN) implemented with Keras. Deployed the best model using flask app.
Developed an accurate and efficient deep learning model for classifying capsule endoscopy images, with the potential to support medical professionals in the diagnosis of GI diseases
This project mimics data incoming from an API. Kafka was used for data streaming and PySpark for data cleaning and validation.
This contains all the visualisations that I created during my Data visualisations using Tableau Public.