`python-m5p` - M5 Prime regression trees in python, compliant with scikit-learn
Sylvain Marié
Algorithms, Predictive Modelling, Science

`python-m5p` is an implementation of the M5P algorithm compliant with scikit-learn.

An Introduction to Inter Process Communication and Synchronization using Python
Tanmoy Bandyopadhyay
Algorithms, Coding / Code-Review, Parallel Programming / Async

Use Python Inter Process Communication and Synchronization techniques effectively

Aspect-oriented Programming - Diving deep into Decorators
Mike Müller
Algorithms, Architecture, Python fundamentals

Functions that take functions and return new functions can be fun. Python's everything-is-an-object principle at work.

Can you Read This? (Or: how I Improved Text Readability on the Web for the Visually Impaired)
Asya Frumkin
Algorithms, Computer Vision, Neural Networks / Deep Learning

I will explain my approach of detecting texts on top of an image background that are unreadable to people with visual impairment. I will explain the challenges I. encountered when using different OCR architectures for this task and talk about the solution I came up with.

Easy and flexible imaging with the Core Imaging Library
Vaggelis Papoutsellis, Dr. Jakob Sauer Jørgensen
Algorithms, Big Data, Math

Core Imaging Library is an open-source, object-oriented Python library for inverse problems in imaging developed by the UK academic network CCPi.

Introducing the Dask Active Memory Manager
Guido Imperiale
Algorithms, Architecture, Backend, Cloud, Data Engineering, Distributed Computing, Parallel Programming / Async

The Active Memory Manager is a new experimental feature of Dask which aims to reduce the memory footprint of the cluster, prevent hard to debug out-of-memory issues, and make worker retirement more robust.

Introduction to Uplift Modeling
Dr. Juan Orduz
Algorithms, Predictive Modelling, Statistics

In this talk we introduce uplift modelling, a method to estimate conditional average treatment effects (CATE) using machine learning estimators.

sktime - python toolbox for time series: advanced forecasting - probabilistic, global and hierarchical
Franz Kiraly
Algorithms, Predictive Modelling, Time Series

The forecasting module of sktime provides a unified, sklearn-compatible, and composable interface. This tutorial covers advanced topics in forecasting using sktime: probabilistic forecasting, and forecasting with panel data, including global/hierarchical forecasting.

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