50+ days of Machine Learning

 Hello :) Today is Day 200! A quick summary of today: creating a project plan, timeline and learning about graph DBs My lab mate and I considered two project ideas. First I will talk and show our plan for the project we chose, and then for the other one which I did a simple demo for. Project idea we chose: Real-time fraud analysis using graph data and graph database My lab mate said he trusts me to choose the technologies for our project and to set up a plan to follow: Training Pipeline Data Collection and Preprocessing: Raw dataset obtained from Kaggle containing transaction data. Raw data is preprocessed before going into the database. Storage in ArangoDB: Transactions are stored in ArangoDB, a popular graph database. Customers and merchants are represented as nodes, and transactions as edges. Graph Neural Network with PyG: PyTorch Geometric (PyG) is used to build and train a Graph Neural Network (GNN) for fraud detection on the graph data. The model is trained on a batch of the data