Multiprocessing in Python
This tutorial is divided into four parts; they are:
Benefits of multiprocessing Basic multiprocessing Multiprocessing for real use Using joblib Link
libraries
15 Open Source libraries for data quality improvement
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FEDOT framework
The folder contains jupyter notebooks with examples of FEDOT framework
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Graph-based Fraud Detection Papers and Resources
A curated list of fraud detection papers using graph information or graph neural networks
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PyTorch VAE
A collection of Variational AutoEncoders (VAEs) implemented in pytorch with focus on reproducibility.
The aim of this project is to provide a quick and simple working example for many of the cool VAE models out there. All the models are trained on the CelebA dataset for consistency and comparison.
The architecture of all the models are kept as similar as possible with the same layers, except for cases where the original paper necessitates a radically different architecture (Ex.
7 Useful Examples of Python’s itertools
The Python itertools library is provides extremely useful utility functions for dealing with iterables.
By becoming fluent in the itertools functions, you can combine them in new ways and use them as building blocks for tackling complex problems in very few lines of code. In this article, you will see 7 practical examples of the applications of itertools functions.
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