The third day of SciPy 2020 was filled with interesting and foundational tutorial content regarding deep learning with a short primer to the PyTorch library and I found the time to watch some interesting SciPy talks from Enthoughts SciPy Youtube channel as well.
Day two of the SciPy 2020 conference was also very informative. Except of some connectivity issues with my internet provider, which lead to missing the latter half of the awesome Dask tutorial and prevented me from listening to other talks, everything went equally smooth.
The notion of tidy data is a concept known from R and used in many available libraries and frameworks today with great success. Tidy data together with proper data types and semantically allowed operations simplifies data science, machine learning and data stewardship by a large margin. In this article we will highlight the core properties of "Tidy Data, Tidy Types, and Tidy Operations" with the help of a concise example and how those properties can be successively achieved and maintained.
'Cli Ranker' is an example commandline tool for document retrieval with personalized individually learned rankings based on query selections. Personalization is achieved by applying principles of reinforcement learning on the problem of learning to rank. This project is accompanying the article 'Personalize Learning to Rank Results through Reinforcement Learning'.
A very quick primer for facilitating understanding and handling of time series and time series decomposition in pandas
An europython beginner talk on the challenges of developing and integrating a Python based unsupervised learning nlp event detection system into a Java project management software for large EPC projects.