jcoombes Goto Github PK

10-time-tracker

4f

Firebase Realtime Database GoJS interaction.

algothon

BlackRock Algorithmic Trading Hackathon.

algothon2018

BlackRock Algorithmic Trading Hackathon. Attempt to use quandl libraries to generate alpha.

asanasequencer

A program to snip and remix yoga videos the way people want.

astronomical-image-processing

awesome-gmtk-game-jam-2021

barabasi_albert

In this project you will study a standard model for a growing network. A simple version ofthis model was described by Barab ́asi and Albert (1999) [1] but it is identical to the citationnetwork model of Price (1965) [2]. In terms of the degree distribution, these models arein turn completely equivalent to the models of Yule (1925) [3] and Simon (1955) [4]. The central idea is that the fat tails seen in many areas could be explained in terms of a “richget richer” principle. This concept goes back to the 19th Century (at least) when Paretonoted that 80% of the land in Italy was owned by just 20% of the population. The idea isso universal that it occurs in many different guises — the “Pareto principle”, the “80-20rule” or even then Matthew effect (Matthew’s gospel “For everyone who has will be givenmore”). For simplicity we will use the terminology of Barab ́asi and Albert [1] who talkaboutpreferential attachmentand we will refer to this model as theBA model.This is so our language matches that of most recent network literature though it fails to acknowledge previous contributions sufficiently [1] A.-L. Barab ́asi and R. Albert,Emergence of scaling in random networks Science,286173 (1999).[2] D. J. de S. Price,The scientific foundations of science policy, Nature,206233–238(1965).[3] G. U. Yule,A mathematical theory of evolution based on the conclusions of Dr.J.C. Willis, F.R.S. Phil. Trans. B,21-8721–87 (1925).[4] H.A. Simon,On a class of skew distribution functions, Biometrica,42425 (1955).

beeware-sudoku-app

BeeWare android app to help solve this challenge -> https://manifold.markets/Mira/will-a-prompt-that-enables-gpt4-to

blainder

A blaine-swiping experience

bsc-project---sound-in-the-oceans

Using 2d hyperbolic Ram modelling.

coefficient-cookiecutter

I want to grab the pyproject.toml so I can build a pre-commit hook

commonsensecode

complexityproject

The aim is to study the Oslo model, which is one of the simplest moddels displauing self-organised criticality. The Oslo model was first published by Christensen et al. (1996) [1, 2, 3]. Despite it's simplicity the Oslo model is rich and non-trivial in its behaviour, and its avalanche-size probability is consistent with the general framework for scaling and data collapse, hat is, the hallmrks of a system displaying self-organised criticality.

computing-year-2

Second year undergraduate Physics computing project.

d2l-jax

Implementation of the Algorithms in Dive into Deep Learning using Jax/Haiku.

dbt-expectations

Port(ish) of Great Expectations to dbt test macros

dbt-fal

do more with dbt. dbt-fal helps you run Python alongside dbt, so you can send Slack alerts, detect anomalies and build machine learning models.

dhl-depo

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django

The Web framework for perfectionists with deadlines.

donald

effectivealltruism

A LLM-powered chrome extension to enable textual style-transfer on Effective Altruism Forum posts.

europython-prague

Large Language Model Zen:

fernleigh

Short and simple financial model - should we invest?

godot-docs

Godot Engine official documentation

goldsmithshack

Repo to help innovate around taboos at Goldsmiths Sex Hack II

imperial-visualizations

Pre-production Research - Which packages are best to use to create and visualise physics simulations in Python (and possibly JS)

insightface

State-of-the-art 2D and 3D Face Analysis Project

ipython-minibook

UPDATE (2015): This is an old repo, go here for the new edition

jcoombes

Personal Repository for github readme.