Thomas Berger
Hi, I’m Thomas Berger! I work as a Machine Learning Engineer at a FinTech company and also teach part-time as a lecturer. I’ve been working with Python for over six years, starting during my studies, where I focused on machine learning. For the last three years, I’ve been applying these skills professionally in my full-time role as a Machine Learning Engineer. I’ve been diving deep into Python for things like machine learning, reinforcement learning, and high-performance computing. I love finding ways to make Python run faster and more efficiently, especially when tackling big data or complex models.
At PyCon, I’ll be talking about high-performance Python and sharing tips and tricks to help you optimize your code for demanding tasks. I’m excited to share what I’ve learned and connect with others in the Python community!
Session
Every Python developer faces performance challenges, from slow data processing to memory-intensive operations. While external libraries like Numba or Cython offer solutions, understanding core Python optimization techniques is crucial for writing efficient code. This talk explores practical optimization strategies using Python's built-in capabilities, demonstrating how to achieve significant performance improvements without external dependencies. Through real-world examples from machine learning pipelines and data processing applications, we'll examine common bottlenecks and their solutions. Whether you're building data pipelines, web applications, or ML systems, these techniques will help you write faster, more efficient Python code.