Marysia Winkels, James HaywardTime Series
From inventory to website visitors, resource planning to financial data, time-series data is all around us. Knowing what comes next is key to success in this dynamically changing world. So join us and learn about time series analysis and seasonality modelling.
Jonathan StriebelData Engineering, Performance
Your data analysis pipeline works. Nice. Could it be faster? Probably. Do you need to parallelize? Not yet. Discover optimization steps that boost the performance of your data analysis pipeline on a single core, reducing time & costs.
Martin ChristenGIS / Geo-Analytics
Create 3DMaps anywhere on the planet using Python and OpenData
Stephannie Jimenez GachaAPIs
Introduction to the consortium of Data APIs, where we will be presenting our motivation, objectives and progress of the standardization process after one year of activity.
Richard PelgrimAPIs, Big Data, Cloud
A hands-on introduction to methods for scaling your data science and machine learning with Dask.
Vaggelis Papoutsellis, Dr. Jakob Sauer JørgensenAlgorithms, Big Data, Math
Core Imaging Library is an open-source, object-oriented Python library for inverse problems in imaging developed by the UK academic network CCPi.
Antoine ToubhansBest Practice, Computer Vision, Data Engineering, Data Visualization, Development Methods, Reproducibility
Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit
Guido ImperialeAlgorithms, Architecture, Backend, Cloud, Data Engineering, Distributed Computing, Parallel Programming / Async
The Active Memory Manager is a new experimental feature of Dask which aims to reduce the memory footprint of the cluster, prevent hard to debug out-of-memory issues, and make worker retirement more robust.
Joris Van den BosscheAPIs, Data Structures
As a pandas user, did you ever run into the SettingWithCopyWarning? Quite likely, and this is one of the more confusing aspects of pandas. But it doesn’t have to be this way! Check my proposal to simplify this aspect of pandas
Prabhant SinghBest Practice, Community, Science
Learn how to create reproducible workflows, benchmarks and studies with openml-python
sktime - python toolbox for time series: advanced forecasting - probabilistic, global and hierarchical
Franz KiralyAlgorithms, Predictive Modelling, Time Series
The forecasting module of sktime provides a unified, sklearn-compatible, and composable interface. This tutorial covers advanced topics in forecasting using sktime: probabilistic forecasting, and forecasting with panel data, including global/hierarchical forecasting.