This repository contains the python notebooks of the tutorial on Federated Learning (FL). It includes examples of how to solve problems either at Horizontal (HFL) or Vertical (VFL) Federated Learning scenarios, using TensorFlow Federated (TFF), Flower and FATE frameworks.

It is divided into different notebooks:

• Comparative study of whether to consider the usage of FL (TFF)
• Use case 1. Image classification using deep learning in HFL (TFF, Flower and FATE)
• Use case 2. Sentiment analysis using deep learning in HFL (TFF and Flower)
• Use case 3. Decision trees in VFL (FATE)
• Use case 4. Introducing differential privacy (TFF)
• Use case 5. Clustering with k-means in HFL (TFF)
• Use case 6. Clustering with k-means in VFL (FATE)