5 Things we've learned building large APIs with FastAPI
Maarten Huijsmans
APIs, Best Practice

5 the common challenges in building FastAPI apps and how to solve them

A Smooth Ride: Online Car Buying and Selling at
Ricardo Kawase, Marlene Hense
Best 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 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 Verbaan
Best 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 Babounikau
Statistics, 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 Boguszewski
Jupyter, 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 Guzharina
Data 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 Stevens
Big 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 Serafini
Packaging, 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 Mora
Algorithms, 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 Farina
Data Engineering, Databases

Lessons learned in 4 years using Postgres in a machine learning project