ParamWebInfo

About the Internship:

Selected intern's day-to-day responsibilities include:

  • Work on REST APIs
  • Engage in server handling and website hosting
  • Write well designed, testable, efficient code by using best software development practices
  • Create a website layout/user interface by using standard HTML/CSS practices

Skill(s) required:

    Java (Learn Java), JavaScript, jQuery, Python (Learn Python), Bootstrap (Learn Bootstrap), PHP(MySQL),Android, Tally (Tally.ERP 9) and HTML, CSS.

Who can apply:

Only those candidates can apply who:

<}ul>

    are available for full time (in-office) internship

    can start the internship between 12th Sep'18 and 17th Oct'18

    are available for duration of 6 months

  • have relevant skills and interests


Additional Information:

    Project Description:

    Venter: Intelligent Complaint Resolution System
    Many civic problems fail to reach resolution because of barriers to submitting a complaint or knowing the right person to contact. As a solution to such problems, Venter is an intelligent complaint management system being developed at IIT Bombay, in collaboration with Microsoft Research which aims to create a platform for categorizing and routing civic complaints to relevant officials. Advances in speech and image understanding have made it possible to create an AI intermediary that speeds up complaint categorization and resolution.

    Venter is currently working with ICMC (I Change My City) which is an online complaint redressal system, where complaints posted on their website are routed to MCGM. Also, Venter has collaborated with SpeakUp, which is an application used to voice the complaints faced by users from corporate firms and supply chains.

    The machine learning model of Venter has the following parts:

    1. For ICMC - Automate the complaint mapping process Venter automates the categorization of complaints posted on ICMC when routed to MCGM, reducing the error in manual mapping - Improve the location pinpointing in complaints The project aims at determining the exact location on the maps, making use of the machine learning model trained to pinpoint the most accurate location in the given