Sponsored Session List
5 Things we've learned building large APIs with FastAPI
Maarten HuijsmansAPIs, Best Practice
5 the common challenges in building FastAPI apps and how to solve them
A Smooth Ride: Online Car Buying and Selling at mobile.de
Ricardo Kawase, Marlene HenseBest Practice, Career & Freelancing, Use Case
Buying or selling a car is a challenging task that requires a lot of difficult decision-making. We will reveal all the "under the hood" data products at mobile.de that support users in making the right decisions.
How a simple streamlit dashboard will help to put your machine learning model in production
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!
My forecast is better than yours! What does that even mean?
Illia BabounikauStatistics, Time Series
Established forecast evaluation procedures often turn out to be inappropriate and biased for modern time series forecasting. I will present the number of forecast evaluations issues and resolutions based on the real use cases of demand forecasting developed within BlueYonder.
Optimize your network inference time with OpenVINO
Adrian BoguszewskiJupyter, Neural Networks / Deep Learning, Performance
Learn how to automatically convert the model using Model Optimizer and how to run the inference with OpenVINO Runtime to infer your model with low latency on the CPU and iGPU you already have. The magic with only a few lines of code.
Overcoming 5 Hurdles to Using Jupyter Notebooks for Data Science, by the JetBrains Datalore Team
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.
Seeing the needle AND the haystack: single-datapoint selection for billion-point datasets
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.
Speeding up Python with Zig
Adam SerafiniPackaging, Performance
Let's speed up Python, with Zig! A tour through Python's C API and packaging challenges...
Unsupervised shallow learning for fraud detection on marketplaces
Andreu MoraAlgorithms, Best Practice, Predictive Modelling
Tune in to learn how @adyen uses ML and open source over python to combat fraud and wrongdoings over large marketplaces such as @gofundme or @eBay
Using a database in a data science project - Lessons learned in production
Jacopo FarinaData Engineering, Databases
Lessons learned in 4 years using Postgres in a machine learning project