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Billy's Projects

dsproj1 icon dsproj1

Process Migration - CMU 15640 Distributed System

dsproj2 icon dsproj2

RMI - CMU 15640 Distributed System Lab2

ensemble-methods-using-r icon ensemble-methods-using-r

I have done my individual project (dissertation) on ensemble methods. In which I first did the background study on different ensemble methods and then implemented Boosting, AdaBoost, Bagging and random forest techniques on underlying machine learning algorithms. I used boosting method to boost the performance of weak learner like decision stumps. Implemented bagging for decision trees (both regression and classification problems) and for KNN classifier. Used random forest for classification trees. I have implemented a special algorithm of boosting called “AdaBoost” on logistic regression algorithm using different threshold values. Then plotted the different graphs like an error rate as a function of boosting, bagging and random forest iterations. Compared results of bagging with boosting. Analysed the performance of classifier before applying ensemble methods and after applying ensemble methods. Used different model evaluation techniques like cross-validation, MSE, PRSS, ROC curves, confusion matrix, and out-of-bag error estimation to estimate the performance of ensemble techniques.

facebooksearch icon facebooksearch

Augmenting Facebook's graph search with functionality for full-text search of a user's posts.

file-and-indexing icon file-and-indexing

The goal of this project is to implement a program that parses an ASCII text-based CSV data file and then transforms that same information to a memory-efficient binary format and writes it to a binary data file. The new binary data file also have multiple index files for efficient record retrieval of values from fields other than the primary key. The program should operate entirely from the command line (no GUI).

foundry icon foundry

The Cognitive Foundry is an open-source Java library for building intelligent systems using machine learning

hackerrank icon hackerrank

My solutions to HackerRank problems (https://www.hackerrank.com)

iedatachallange-django-analytics-project icon iedatachallange-django-analytics-project

IE 2nd term project prototype application based on Telefonica Mobility and BBVA Credit Card Payments. Provider data is strictly disclosed; but you can use the code in any purpose you desire. MVC stack framework using python Django. Api integrations with Expedia and Twitter Streaming API. Important work on TripAdvisor webscraping. NLP (NLTK) for Topic based sentiment analysis(Trip Advisor Reviews), Timeseries forecasting, Recommendation Engine, Leaflet Data Visualization, NetworkX SNA (python and JS). BBVA data is neglected because of lack of data integrity and necessary categories. I hope this work can be helpful to practicioners of Django framework and analytics. This application is developed in a very short term with Agile methodology, therefore it is normal that there are problems and inconsistencies of code quality. For example we tried to use mongoengine and Django framework document models as a common data source; but we faced with difficulties time to time because of lack of accurate documentation in web. Whenever we resolved we followed the accurate coding practice. Please followup the model usage practice in the last view in views.py to comply with MVC, do not use pymongo directly. Mongoengine will provide features like DBConnectionPooling that will facilitate a scalable architecture.

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