The author discusses a shift in approach to clustering mixed data, advocating for starting with the simpler Gower distance metric before resorting to more complex embedding techniques like UMAP. They introduce 'Gower Express', an optimized and accelerated implementation of Gower.
Pandas 3.0 will significantly boost performance by replacing NumPy with PyArrow as its default engine, enabling faster loading and reading of columnar data.
Learn how to use Autoencoders to detect anomalies in time series data in a few lines of code.
Stumpy is a Python library designed for efficient analysis of large time series data. It uses matrix profile computation to identify patterns, anomalies, and shapelets. Stumpy leverages optimized algorithms, parallel processing, and early termination to significantly reduce computational overhead.
