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Ian Madlenya's Projects

steambot icon steambot

Automated bot software for interacting with Steam Trade

steward icon steward

A stock portfolio manager that provides neural net based short-term predictions for stocks and natural language processing based analysis on community sentiments.

stock icon stock

Stock market analysis and modeling

stock-analysis-2 icon stock-analysis-2

An app built on python's pyramid framework that performs data analysis and machine learning on stock data.

stock-app icon stock-app

Desktop class stock tracking application developed with AngularJS.

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💰🤑Predictive model for stock prices🤑💰

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Stock Hawk is the fourth project in Udacity's Android Developer Nanodegree.

stock-market-application icon stock-market-application

A project developed during the Software Requirements and Analysis course. This application is developed using C# and implements the Observer design pattern. This application provides the ability to buy and sell stocks (hypothetically) and the information will be updated in a central information window.

stock-market-prediction-using-intrinsic-valuation icon stock-market-prediction-using-intrinsic-valuation

This is a data mining project carried out using Rapid Miner tool. This project is part of my ongoing Independent study and research in Data Mining. A data mining model in Rapid Miner tool was created, and Yahoo API as a data source was used. We trained on past stock market data with Stock Price as target and different Intrinsic Values which influence that stock price. Our model used two predictive algorithms and gave results of top 50 performing stocks, which should be bought. We have build a data mining model which uses the absolute stock valuation method(Intrinsic Stock Valuation) for determining if the stocks are undervalued or overvalued.

stock-market-prediction-using-natural-language-processing icon stock-market-prediction-using-natural-language-processing

We used Machine learning techniques to evaluate past data pertaining to the stock market and world affairs of the corresponding time period, in order to make predictions in stock trends. We built a model that will be able to buy and sell stock based on profitable prediction, without any human interactions. The model uses Natural Language Processing (NLP) to make smart “decisions” based on current affairs, article, etc. With NLP and the basic rule of probability, our goal is to increases the accuracy of the stock predictions.

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