tush1r

algopricer

Automatically exported from code.google.com/p/algopricer

BinomialOptModel

A python program to implement the discrete binomial option pricing model

code

ActiveState Code Recipes

cpp-for-financial-engineers

Automatically exported from code.google.com/p/cpp-for-financial-engineers

cqf-final-project

CQF Final Project

quantstats

Portfolio analytics for quants, written in Python

Data-Science--Cheat-Sheet

Cheat Sheets

disruptor

Automatically exported from code.google.com/p/disruptor

disruptor-1

High Performance Inter-Thread Messaging Library

FAKE

FAKE - F# Make

fsharpdaybyday

Learn F# in tiny increments

go

The Open Source Data Science Masters

google-api-python-client

Automatically exported from code.google.com/p/google-api-python-client

google-motion-charts-with-r

Automatically exported from code.google.com/p/google-motion-charts-with-r

mrec

A recommender systems development and evaluation package by Mendeley

Node-Pool

Introduction to Node.js For .Net Developers

oreilly-bootcamp

Materials for Learning DS O'Reilly Bootcamp

Publications-Medium

pydata-book

Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

pyfin

Basic options pricing in Python

python-recsys

A python library for implementing a recommender system

Python_Option_Pricing

An libary to price financial options written in Python. Includes: Black Scholes, Black 76, Implied Volatility, American, European, Asian, Spread Options

pytorch-tutorial

PyTorch Tutorial for Deep Learning Researchers

Quantsbin

Quantitative Finance tools

skillsnetwork

spyder

Official repository for Spyder - The Scientific Python Development Environment

stat-learning

Notes and exercise attempts for "An Introduction to Statistical Learning"

Surprise

A Python scikit for building and analyzing recommender systems

theMLbook

The Python code to reproduce the illustrations from The Hundred-Page Machine Learning Book.

VaR

Simple VaR calculation in Python, both for single value and VaR series in time. Supported formulas at the moment include: Parametric Normal, Parametric EWMA, Historical Simulation and Filtered Historical Simulation with EWMA.