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Andrew Conti's Projects

bluebook icon bluebook

This IPython Notebook contains a quantitative pricing model created for Fast Iron in the Kaggle competition 'Blue Book for Bulldozers'. The model predicts the sale price of a particular piece of heavy equipment so that Fast Iron can create a 'Blue Book' to enable customers to valuate their heavy equipment fleet at auction. Here python is used as a medium to apply supervised and unsupervised machine learning techniques to explain 88.90% of the variance observed in the training set and score an RMSLE of 0.745 when predicting values on the test set. In this competition 590 data scientists created predictive models based on a 'training dataset', provided by Fast Iron, and then used those models to predict sale prices on a 'test set' to compete for a $10,000 dollar award for the team or individual with the most accurate model. The model and methods used for my entry, which scored in the upper 20%, is shown in BlueBook.ipynb.

boa_elevator icon boa_elevator

My solution to reverse engineering an optimized and non optimized elevator algorithm for BOA

chat icon chat

basic socket.io example.

clear-dictionary icon clear-dictionary

If you're like me, you often add a misspelled word to computer's dictionary by mistake. Fix it easily now.

clock icon clock

a minimalistic clock in d3.js

cookiecutter icon cookiecutter

A command-line utility that creates projects from cookiecutters (project templates). E.g. Python package projects, jQuery plugin projects.

country-ip-blocks icon country-ip-blocks

CIDR country-level IP data, straight from the Regional Internet Registries, updated hourly.

credstash-set icon credstash-set

Load credentials into your credstash tables from an env file.

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