Data Handling
6 talks from the 2022 edition.
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Fundamentals of relational databases ▶ Recording 📝 Transcript
Katharina Rasch
Are you somewhat comfortable with using SQL to access data, but are curious to know what happens behind the scenes when you send off your query? Then this is the talk for you! Relational database systems have been...
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PPML: Machine Learning on Data you cannot see ▶ Recording 📝 Transcript
Valerio Maggio
What if I tell you that you can run a complete ML pipeline on private data, without any anonymisation, nor even accessing the data in the first place? 🧐 And what If I also tell you that you can do that with no...
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Processing Open Street Map Data with Python and PostgreSQL ▶ Recording 📝 Transcript
Travis Hathaway
The Open Street Map (OSM) project is a global, open-source database with over 50GB of data, and this number grows everyday with every user submission. With such a big data set out there, also comes a huge potential...
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Squirrel - Efficient Data Loading for Large-Scale Deep Learning ▶ Recording 📝 Transcript
Dr. Thomas Wollmann
Data stall in deep learning training refers to the case where combined throughput of data loading and transformation is less than the consumption rate of the model, leading to idling of expensive GPU resources and...
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Using a database in a data science project - Lessons learned in production ▶ Recording 📝 Transcript
Jacopo Farina
Storing and processing data in a relational database for a machine learning project presents unique challenges. Processing large volumes can take long, source data has to be continuously ingested and kept up to date,...
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What are data unit tests and why we need them ▶ Recording 📝 Transcript
Theodore Meynard
I will introduce the concept of data unit tests and why they are important in the workflow of data scientists when building data products. In this talk, you will learn a new tool you can use to ensure the quality of...