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Trading strategy for the S&P 500 index based on ARIMA models.
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2D DEM simulation showing brazil nut effect
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This includes an implementation of Conditional Variational Autoencoders (CVAE).
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Machine learning model that uses signatures to recognise handwritten signatures.
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ESGI116 Technip Project on Umbilical Optimised Design
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Use of genetic algorithms for a simple trading strategy, in C++.
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Signature-based machine learning model that predicts, given daily data of a stock (more specifically, the evolution of its price and volume) which country the stock trades in.
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This repository contains the updated code that is being used in the Machine Learning reading group organised by Terry Lyons.
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MonteCarlo and Arima for stock selection
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project with maria
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Pair trading in C++
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Predicting Mortality of ICU Patients: the PhysioNet/Computing in Cardiology Challenge 2012
Challenge website: https://physionet.org/challenge/2012