Clindo Devassy

The title of my thesis is user-centered anomaly detection in network data. The network anomaly detection is done using the different machine learning algorithms. I used python, sci-kit learn for creating the machine learning models, Elasticsearch for data storage and retrieval, HTML5, Reactjs, d3js,dcjs for data visualization and Flask framework for building REST services.

As a working student I have to do: * Data preprocessing using python and pandas * Implement machine learning models for predictions

As a working student I had to : * Implement visualizations using ReactJS, d3Js,visJs * Use NodeJs, express framework, MongoDB,Elasticsearch

As a programmer Analyst I had to do: * Analysis, design, development and implementation of applications in Java and Android. * Application development with HTML5, AngularJS. * Designed,developed and implemented data migration (ETL) of critical database from MSSQL to MySQL. * Fine tuned and improved performance SQL queries running in MySQL, SQL Server 2008 and SQL Server 2012 * Deployed applications with application servers Apache Tomcat 7.0 and IBM Websphere 8.0