In this series of liveProjects, you’ll extend and upgrade basic machine learning techniques like linear regression to build a powerful tool that can make personalized predictions of an individual's COVID-19 infection status. You will apply federated learning techniques to train a machine learning system on a (fictional) dataset of smart phone data. Federated learning is a new ML paradigm used for the collaborative training of models from heterogeneous and distributed data such as audio recordings generated by smartphones. This liveProject series will teach you how to use federated learning techniques to exploit the intrinsic network structure (“contact networks”) between audio recordings in order to learn optimal model parameters for each individual. Federated learning techniques are privacy-friendly as they do not require the sharing of sensitive private data, such as audio recordings of smartphone users.
This series of liveProjects is for Python data scientists interested in applying big data analytics to public healthcare. To begin this liveProject you will need to be familiar with the following:
In this series of liveProjects, you’ll learn to develop powerful and personalized machine learning applications for tracking infections. You’ll also utilize the new federated learning ML paradigm that learns ML models from decentralised data via distributed computing environments.
geekle is based on a wordle clone.