This series will explore various topics and techniques in machine learning, arguably the most talked-about area of technology and computer science over the past several years. We’ll begin, in this article, with an extended “case study” in Python: how can we build a machine learning model to detect credit card fraud?
Nir Cohen describes Wagon, which takes Python wheels, packages them together, adds metadata, and allows for offline extraction and installation.
Python Playground provides a large and varied collection of projects to show how Python can be used in such different contexts as ASCII art, birds simulation, interfacing to Raspberry Pi, and more.
InfoQ speaks with Brett Slatkin, senior staff software engineer at Google and author of Effective Python.
Overwhelmed the flood of new languages and libraries? JNBridge helps alleviate developer fatigue by mixing the libraries you know with the language you are learning.
"BDD In Action" is a book that aims to cover the full spectrum of BDD practices from requirements through to the development of production code backed by executable specifications and automated tests. 4
By combining asynchronous I/O with a shared-nothing architecture, PyParallel research project is able to execute code in a parallel context faster than it can using CPython’s normal interpreter. 1
Zato is an open-source ESB and application server written in Python. It is designed to integrate systems in SOA and to build backend applications (i.e. API only). 2
Despite the fact that Python is not a pure-functional programming language, it's multi-paradigm and it gives you enough freedom to take advantage of the functional programming approach.
Christopher Moyer has written a new book, which revolves around architecture and design patterns that can be used to build and host scalable, reliable applications in the cloud.