PyData
15 talks in this track
Let them explore! Building interactive, animated reports in Streamlit with ipyvizzu & a few lines of Python
talkBuilding Streamlit apps that enable business users to explore data on their own is an excellent way to support data-driven decision-making in any organization. Pair this up with the animated transitio...
How to Build a Data Science Portfolio That Will Make Recruiters Swipe Right
talkBuilding a strong data science portfolio can be a daunting task, especially for those just starting out in the field. In this talk, we will explore the essential elements of a successful data scienc...
Is it the end for Apache Airflow?
talkThe talk will introduce Apache Airflow and its competitors. The main goal of the talk is to showcase how Airflow adapted to the ever-changing data space. Comparison and feature exploration would be or...
Similarity search in practice or how AI can help in everyday’s life
workshopAI technologies brough the ability to construct the data in new light. Search engines learn to search not by keywords but by semantic information, the same goes for image or audio search. In this talk...
Portable Feature Engineering with Hamilton: Write Once, Run Everywhere
talkMost data transformations are written twice. In the field of feature engineering for Machine Learning, data scientists regularly have to build, manage, and iterate on batch jobs, then translate those ...
pandas 2.0 and the Arrow revolution
talkpandas 2.0 has recently been released, and one of the key features is a greater support of the Apache Arrow in-memory format. While the change is somehow internal, it opens a wide range of possibiliti...
Production ready Machine Learning pipelines using ZenML for MLOps management
talkMLOps tools today are dime a dozen, but do you really need everything to build your machine learning pipelines? If you are just getting started you do not need an army of tools to set up your ML pipel...
Driving down the Memray lane - Profiling your data science work
talkIn this talk, we will be exploring what memory profiling is, and how it can help with data science work. We will start the talk with a basic explanation of how Python arrange memories for various obje...
Analyze your data at the speed of light with Polars and Kedro
workshopWriting maintainable data science code is a big topic, and different people have different opinions on the best ways to do it. Wouldn't it be nice if there was an opinionated framework to set some str...
Serverless billion-scale vector search for AI applications
talkFrom recommendation systems to LLM-based applications, vector search is a critical component of the modern AI workflow. Existing vector solutions are complicated to use, hard to maintain, and cost too...
MLOps Fundamentals or What Every Machine Learning Engineer Should Know
talkIn this talk, we will explore the rapidly evolving field of MLOps. I will delve into best practices and tools that are essential for building and deploying machine learning models. I will cover topics...
Unlocking the Power of PySpark: A Comprehensive Workshop
workshopAre you struggling with big data in your business? Join us to discover how PySpark can help you solve your problems efficiently and effectively. In this workshop, we will revisit the key concepts of P...
The Ultimate Matchmaker: Building Recommender Systems with TensorFlow
workshopAre you curious about how recommendation engines work? In this workshop, we'll dive deep into the world of TensorFlow Recommender Systems, exploring the fundamental concepts, techniques, and tools nee...
Polars: done the fast, now the scale
talkDataFrame abstractions are one of the favorite data structures of many data scientists, data-engineers and programmers in general. They offer flexibility and intuitive reasoning on top of query proces...
How we predict purchases in mobile games
talkMore than 5 million people play Nordcurrent mobile games every month. The specificity of free-to-play games is that less than 10% of players make purchases. It is essential to retain paying players an...