PyData London 2024

The proposed presentation offers a comprehensive exploration of the fundamental principles of Quantum Machine Learning (QML), focusing on its practical applications, current challenges, and future prospects. Throughout the talk, we will address the following key issues:

1. Introduction to Quantum Computing: We will define the concept of quantum computing and illustrate its utility and potential. We will explore whether the time has come to use this technology and the challenges and opportunities within the realm of quantum technology.
2. Programming and Operations Basics: We will explain how to program a quantum computer and discuss the Python libraries available to facilitate the approach to this innovative technology.
3. Fundamentals of Quantum Machine Learning: We will delve into the advantages offered by Quantum Machine Learning compared to classical machine learning, highlighting the peculiarities that characterize this emerging discipline.
4. Quantum Computers and Libraries: We will analyze the tools available to Python users for experimenting with quantum computers and how to integrate them into the learning and development process.
5. Approach to the Topic: We will provide practical advice on how to approach this subject, illustrating effective ways to start learning and using Quantum Machine Learning.

The target audience consists of professionals, students, and machine learning enthusiasts interested in exploring the potential of QML, without necessarily possessing an in-depth knowledge of quantum physics. Our goal is to offer a comprehensive and accessible overview of this fascinating interdisciplinary field, encouraging involvement and active learning in this innovative sector.