Topics

• Optimizing Python Code
  By: Anna Astori
  Experience Level: Novice
  Length: 15 Minutes
  Description:

  Have you experienced issues with your Python code while wrangling new data sets and crunching big numbers? Have you wondered what are the places where you could make your Python scripts run faster? Let's talk! Today, I will cover a few options to speed up your data processing operations. This talk can be especially valuable for those who are just starting out in Data Science and Python 
  development. Nonetheless, everyone interested in efficient Python is welcome!

• How to build a Recommender System from scratch in (mostly) Python
  By: Aabir Abubaker Kar
  Experience Level: Novice
  Length: 60 Minutes
  Description:

  A recommender system (recsys) is a no-brainer investment for any service that offers users a wide choice of items. This talk will teach you how to design and build one yourself, informed by lessons learnt shipping a recsys to 5 million MAUs. We'll start with the simplest heuristics and ML models that do the trick, focusing significantly on system design. We'll discuss how to compute, store, and serve recommendations - and also how to build a robust data system with long-term value. We can also nerd out about machine learning and idea jam at the end.
  
  I write at bakerwho.github.io and tweet at @bakerwhodata sometimes. HMU