Stochastic regression imputation can be considered a refinement of regression imputation because it addresses the correlation bias by adding noise from the regression residuals to the missing value estimations. This post discusses the advantages of stochastic regression imputation with examples in Python.
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.
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.