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Hamilton Wong's Projects

redis-cache icon redis-cache

A persistent object cache backend for WordPress powered by Redis. Supports Predis, PhpRedis, HHVM, replication and clustering.

ripple-lib icon ripple-lib

A JavaScript API for interacting with the XRP Ledger in Node.js and the browser

rippled icon rippled

Decentralized cryptocurrency blockchain daemon implementing the XRP Ledger in C++

roq-api icon roq-api

The Roq C++20 API used for Live Cryptocurrency Algorithmic and High-Frequency Trading as well as for Back-Testing and Historical Simulation

roq-samples icon roq-samples

How to use the Roq C++20 API for Live Cryptocurrency Algorithmic and High-Frequency Trading as well as for Back-Testing and Historical Simulation

sfa icon sfa

Scalable Time Series Data Analytics

socket.io.tests icon socket.io.tests

A basic example of testing node apps that use socket.io using mocha and chai

sol icon sol

A sunny little virtual machine

solidity icon solidity

Solidity, the Contract-Oriented Programming Language

statistical_modeling_for_time_series_forecasting icon statistical_modeling_for_time_series_forecasting

The S&P 500 Market Index is analysed using popular statistical models such as SARIMA, ETS and GARCH. Additionally, a powerful open source forecasting package from Facebook, called Prophet, is also used.

stellar-core icon stellar-core

stellar-core is the backbone of the Stellar network. It maintains a local copy of the ledger, communicating and staying in sync with other instances of stellar-core on the network. Optionally, stellar-core can store historical records of the ledger and participate in consensus.

stock-price-predictor icon stock-price-predictor

This project seeks to utilize Deep Learning models, Long-Short Term Memory (LSTM) Neural Network algorithm, to predict stock prices.

stockpredictionai icon stockpredictionai

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

tinyvm icon tinyvm

TinyVM is a small, fast, lightweight virtual machine written in pure ANSI C.

tradingneuralnetwork icon tradingneuralnetwork

A network tries to predict movements in stock prices based on a picture of a time series stock price.

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