Jovan Veljanoski
Jovan is a senior data scientist at Tiqets, where he creates predictive models and recommender systems centered around the e-commerce domain. Working mostly with Python in the Jupyter/PyData ecosystem, he has considerable experience in creating dashboard, clustering analysis and predictive modeling. Jovan has a PhD in Astrophysics, is a co-founder of vaex.io, and is interested in novel machine learning technologies and applications.
Sessions
Vaex is an incredibly powerful DataFrame library that allows one to work with datasets much larger than RAM on a single node. It combines memory mapping, lazy evaluations, efficient C++ algorithms, and a variety of other tricks to empower your off-the-shelf laptop and make it crunch through a billion samples in real time.
A common use-case for Vaex is as a backend for data apps, especially if one needs to process, transform, and visualize a larger amount of data in real time. Vaex implements a number of features that have been specifically designed to improve performance of data hungry dashboards or apps, namely:
- caching
- async evaluations
- early stopping of operations
- progress bars
In this talk we will showcase how you can use these features to build efficient dashboards and data apps, regardless of the data app library you prefer using.