Gaming with mapbox
The idea for this project came when I was brainstorming new project ideas with a colleague. We wanted to combine the power of Operational Transforms with mapbox’s API. Ultimately however we had no need for Operational Transform.
The idea for this project came when I was brainstorming new project ideas with a colleague. We wanted to combine the power of Operational Transforms with mapbox’s API. Ultimately however we had no need for Operational Transform.
For the first part of this post I invite you to take a look at my friend Satyajit’s post where he describes the data layout of OSM and talks about rendering it in matplotlib.
This is my attempt at creating a model which could predict the presence of the west nile virus from a given dataset. The problem was originally presented as a kaggle competition running from April to June of 2015. The full description of the problem can be found here.
The data was collected from mode analytics. It shows the crimes reported to San Francisco Police Department from Nov 1 2013 to Jan 31st 2014. For every crime that was reported the data includes:
Virtual Machines are proxies for real or hypothetical computers. Their uses are varied, sometimes a VM might be needed to simulate hardware that does not yet exist (might never exist) or sometimes to run Windows on a Mac environment. These VMs are better known as system virtual machines and this is the last time we’ll talk about them in this post.
Every one who dreams of calling himself a computer scientist ought to know a few things in his chosen profession. Regular expressions happen to be one of them, they appear deceptively simple when seen from the end of a good text editor, but if you went behind the curtains you’d find an intricate dance of some of the core concepts of computer science.
Who needs shadows anyway? Shadows help in maintaining the illusion of reality. Take for example this image
Raison d’etre
This is faking…with style
Distributed ray tracing does not mean ray tracing on a distributed system. The term here means distributing the rays by an analytic function, say a cone. The original paper for this can be found here.