Scientific Software

Jaccs allows you to pull data from JSON objects using string Python expressions. This is expected to be most useful for combining specifications stored in external text files (say JSON or YAML) with data objects in Python.

PyMOTW-3 is a series of articles written by Doug Hellmann to demonstrate how to use the modules of the Python 3 standard library. It is based on the original PyMOTW series, which covered Python 2.7.

How To Search and Download Satellite Imagery This tutorial shows you how to search EarthExplorer using latitude and longitude coordinates.

DeepMind Lab is a 3D learning environment based on id Software's Quake III Arena via ioquake3 and other open source software. DeepMind Lab provides a suite of challenging 3D navigation and puzzle-solving tasks for learning agents. Its primary purpose is to act as a testbed for research in artificial intelligence, especially deep reinforcement learning.

NetworkX is a Python language software package for the creation, manipulation, and study of the structure, dynamics, and functions of complex networks.

This blog post aims to explain the “theory” behind version control (Git and Github) in plain English so that you understand the big picture of how software engineers work. No code. Nothing to download. No muss. No fuss. Just words and some not-so-pretty doodles drawn by yours truly.

Python TensorFlow code for casting the design of an optimization algorithm as a learning problem in contrast to hand-designed algorithms. See the paper Learning to Learn by Gradient Descent by Gradient Descent (https://arxiv.org/pdf/1606.04474v2.pdf).

An open source python package for simulation and gradient based parameter estimation in geophysical applications.

A web-based GIS application designed to support resource assessment and data exploration associated with wind development. Hosted by the National Renewable Energy Laboratory of the U.S. Dept. of Energy.

Stanford CoreNLP provides a set of natural language analysis tools. It can give the base forms of words, their parts of speech, whether they are names of companies, people, etc., normalize dates, times, and numeric quantities, mark up the structure of sentences in terms of phrases and word dependencies, indicate which noun phrases refer to the same entities, indicate sentiment, extract particular or open-class relations between mentions, etc.

A software platform for evaluating and training intelligent agents across the world’s supply of games, websites and other applications.

Universe allows an AI agent to use a computer like a human does: by looking at screen pixels and operating a virtual keyboard and mouse. We must train AI systems on the full range of tasks we expect them to solve, and Universe lets us train a single agent on any task a human can complete with a computer.

Computer vision is an exciting and quickly growing set of data science technologies. It has a broad range of applications from industrial quality control to disease diagnosis. I have dabbled with a few different technologies that fall under this umbrella before, and I decided that it would be a worthwhile endeavor to rapid prototype an image recognition web application that used a neural network.

Want to learn programming with Python in ArcGIS but don’t know where to start? This guide tells you what to do to become a confident ArcGIS Python scripter and programmer.

A toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents everything from walking to playing games like Pong or Go.

The entire Pro Git book, written by Scott Chacon and Ben Straub available online in HTML, PDF, ePub, and Mobi formats.

The Visualization Toolkit (VTK) is an open-source, freely available software system for 3D computer graphics, image processing, and visualization. It consists of a C++ class library and several interpreted interface layers including Tcl/Tk, Java, and Python. VTK supports a wide variety of visualization algorithms including scalar, vector, tensor, texture, and volumetric methods, as well as advanced modeling techniques such as implicit modeling, polygon reduction, mesh smoothing, cutting, contouring, and Delaunay triangulation.

A collection of tutorials for learning how to use TensorFlow for neural networks, from basic machine learning and neural networks to convolutional neural networks to recurrent neural networks and more.

TensorBoard has a built-in visualizer, called the Embedding Projector, for interactive visualization and analysis of high-dimensional data like embeddings. It is meant to be useful for developers and researchers alike. It reads from the checkpoint files where you save your tensorflow variables. Although it's most useful for embeddings, it will load any 2D tensor, potentially including your training weights.

A handy online application for editing GeoJSON attributes.

This is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material.