Event: PyConDE & PyData Berlin | Date: Tuesday, April 23th 2024

Talk: Link

Abstract

The human ambitious desire to get rich without effort has been a major driving force behind the popularity of cryptocurrencies like Bitcoin and Ethereum. However, their high volatility makes them too unpredictable, and keeping track of our investment gains and losses over time can be tedious, if not boring.

In this talk, we will define the different components necessary to build a personalized Bitcoin (BTC) virtual assistant in Python. The assistant will help you analyze your transaction history, estimate future BTC prices, and calculate the future value of your holdings based on these predictions. It will be powered by LLMs and will make use of a recent technique called Function Calling to recognize the user intent from the conversation history.

The ML system will be built in Python, following the best practices of the FTI (feature/training/inference) pipeline architecture, on top of the open-source Hopsworks platform which will provide the necessary ML infrastructure such as a feature store, model serving, and a model registry.