In this series, we give an introduction to some powerful but generally applicable techniques in machine learning. These include deep learning but also more traditional methods that are often all the modern business needs. After reading the articles in the series, you should have the knowledge necessary to embark on concrete machine learning experiments in a variety of areas on your own.
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?
In this series we explore ways of making sense of data science - understanding where it’s needed and where it’s not, and how to make it an asset for you, from people who’ve been there and done it.
A quick introduction to the machine learning field, exploring both supervised and unsupervised approaches. 2
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