November Python Meetup: Performance, easy ML deployments

The November Python meetup features 3 talks and will be hosted by Volkswagen Data:Lab. Bring your friends! We have a huge space, it will be an epic gathering 🎉
The plan:

👉 18:30 Doors open, snacks, drinks

👉 19:00 "An introduction to Numba - Speeding up your Python code"

The common recommendation for writing high-performance Python code is to avoid loops. Instead one should rely on libraries like NumPy or pandas for performance-critical parts. If a problem cannot be addressed by those libraries, the only alternative for a long time was to write the core parts directly in a compiled language, such as C, C++, or Cython. Thanks to the Numba project there is an attractive alternative. As its core, Numba is a JIT compiler for Python. With a simple API and wide support for common Python features, it is easy to use and highly efficient.

In this talk, I will give an overview of Numba and show how it can help in Data Science projects. Based on examples, I will first motivate the need for custom loops. Next, I will introduce Numba, its API, and how it applies to the given examples. Finally, I will showcase some of its more advanced features, such as JIT classes and CUDA support.

Christopher is working as Data Scientist for Volkswagen Data:Lab. Trained as Physicist, he is now focusing on the application of machine learning to engineering topics. Within this application domain, he is working at the intersection of modern machine learning and classical engineering approaches

👉 19:40: "Building user-friendly CLI with Click"
We see how to create simple, yet expressive CLI with Click. I will show a few tricks and patterns on how to keep your code clean and extensible.

Wiktor Jan Jurasz is a data engineer at KI Labs working on open source ML platform - kaos (https://github.com/KI-labs/kaos) and doing masters in data engineering and analytics at TUM.

👉 20:10 Joshua Friedman: "Kaos – how we simplified ML deployment"

This talk will be rather ad-hoc but will focus on kaos – a new open-source platform for deploying scalable reproducible machine learning workflows in your own private environment. It will focus on the what, why, and how of kaos, and finally how it has been used to solve some important problems… how to build a smarter BeerBot!

Joshua is a Data Engineer turned Data Product Manager at KI labs. His background is extremely atypical spanning many fields - Civil Engineering to Coastal Engineering to Remote Sensing to Big Data to _______. Joshua also enjoys hacking on his pi(s), automating life with shortcuts and putting QR codes everywhere.

👉 20:30: Drinks & Networking

See you!
-Anton & Dibya ✌️