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10am ET

The Download - Tech Talks

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Watch Recording / View Slides

Guest Speakers and subjects: 

  1. Yash Jain - Bachelor of Engineering (Computer Engineering), University of Mumbai
    HPCC Systems Intern Project: Cluster Deployment with Juju Charm

    Yash
    is a student at the University of Mumbai, studying for a Bachelor of Engineering (Computer Engineering). Yash joined the HPCC Systems team in 2019 to work on a project titles Cluster Deployment with Juju charm. The aim of this project is to write reactive charms using the charm helper framework along with tests in amulet. Previously, Yash has worked as an intern with the open mainframe project porting Kata Containers to the mainframe platform. His work was presented at the Open Source Summit EU held in October 2018 in a joint talk with the other interns. He has also worked on the development of a content management system at the VES Institute Of Technology, He has been ranked 280 in TCS Codevita, a competitive programming competition, in 2017.

    The aim of this project is to deliver charms for the HPCC Systems platform and HPCC Systems plugins, ported to the Charms helper framework with corresponding tests in amulet.

  2. Akshar Prasad - HPCC Systems Intern 2019, RVCE
    HPCC Systems Intern Project: Fraud Detection in Value Based Cards

    Akshar is a student at the  Rashtreeya Vidyalaya College of Engineering (RVCE), studying a BTech in Computer Science.

    The full title of this project is 'Detection of fraud in stored-value cards by applying CNN and Random Forest machine learning models on transactional data to classify a transaction as “Fraudulent” or “Not fraudulent'. These methods will be compared for efficacy. In his proposal, Akshar pointed out how the features of a stored value card, while attractive to consumers from data privacy and anonymity points of view, are also susceptible to fraud. Identifying fraudulent methods in a cost effective and timely manner is a challenge for companies who supply these cards.

    Akshar is seeking to prove that the machine learning model he has chosen provides an easier method of solving the problem of identifying anomalies quickly that may suggest a fraudulent transaction has taken place.

     
  3. A Suryanarayanan - HPCC Systems Intern 2019, RVCE
    HPCC Systems Intern Project: Evaluation of Machine 
    Learning Algorithms

    Surya is a student at the  Rashtreeya Vidyalaya College of Engineering (RVCE), studying a Bachelor of Engineering (Computer Science).

    Surya's project involves providing additional evaluation methods for our Machine Learning Library, including running comparisons with existing benchmarks, the addition of new evaluation metrics and the enhancement of performance checking. These evaluations will help the performance of the models and enhance their ability to choose the appropriate method for the given data. The aim is to provide an evaluation tool that integrates well with features such as the Myriad Interface.

  4. Sathvik K R - HPCC Systems Intern 2019, RVCE
    HPCC Systems Intern Project: Interfacing Octave with  ECL

    Sathvik is a student at the  Rashtreeya Vidyalaya College of Engineering (RVCE), studying a Bachelor of Engineering (Computer Science).

    The aim of this project is to support Octave by allowing the embedding of Octave database queries within ECL code. This will be done with the help of simple wrapper classes to handle scalar values and structured data, including multi-threaded access from the ECL side. This will add to the growing list of embedded languages and datastores we currently support.
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