Emeli DralBest Practice, Data Visualization, Statistics
When ML model is in production, you might encounter data and prediction drift. How exactly to detect and evaluate it? I'll share in this talk.
Philipp Rudiger, Maxime LiquetData Visualization, Jupyter, Science
Do you use the .plot() API of pandas or xarray? Do you ever wish it was easier to try out different combinations of the parameters in your data-processing pipeline? Follow this tutorial to learn how to easily build interactive plots and apps with hvPlot.
Maria MestreData Engineering, Data Visualization, Natural Language Processing
Data labelling should not be a waterfall task. Label your data significantly faster with weak supervision (https://github.com/dataqa/dataqa)
Antoine ToubhansBest Practice, Computer Vision, Data Engineering, Data Visualization, Development Methods, Reproducibility
Flexible ML Experiment Tracking System for Python Coders with DVC and Streamlit
Daniël Willemsen, Welmoet VerbaanBest Practice, Data Visualization, Predictive Modelling
Have you struggled getting your valuable machine learning model into the hands of users? A simple streamlit monitoring dashboard can help!
Alena GuzharinaData Visualization, Jupyter, Reproducibility
Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains @Datalore Team Join our talk to discuss setting up environments, working with data, writing code without IDE support, and sharing results, as well as collaboration and reproducibility.
Daniel RinglerData Visualization, Jupyter, Python fundamentals
Sankey Plots in Python? Get an introduction on how and when to use them.
Jean-Luc StevensBig Data, Data Visualization, Jupyter
Building simple custom interactive web dashboards that display millions or billions of samples while giving access to each individual sample.
Jessica Greene (she/her), Vanessa AguilarData Visualization, DevOps, Performance
We know what your app did last summer. Do you? Join us for this practical & theoretical session if you’re looking to grasp the key concepts of observability, useful metrics, and ensuring operational excellence for your Python applications using Prometheus!
Jannis LübbeAPIs, Data Visualization, Use Case
Streaming sensor data to multiple end devices using FastAPI and websockets.
Larissa HaasData Visualization, Ethics (Privacy, Fairness,… ), Transparency / Interpretability
XAI meets NLP - approaches, workarounds and lessons learned while making an NLP project explainable
Paula Gonzalez AvalosData Visualization, Predictive Modelling
Your data, your insights: 3 examples to illustrate how we can apply common data science libraries together with data shared via mobile apps or collected manually to build little data visualization projects that provide unique, contextual and intmiate insights.