Lavanya Sopanahalli Devaraju

Encouraging manager and analytical problem-solver with talents for team building, leading and motivating, as well as excellent customer relations aptitude and relationship-building skills. Proficient in using independent decision-making skills and sound judgment to positively impact company success. Dedicated to applying training, monitoring and morale-building abilities to enhance employee engagement and boost performance.

Programming Languages - C, C++, Python

Operating Systems - Linux, Windows

Office tools - MS word, Excel, PowerPoint, Outlook

AUGUST2017-NOVEMBER2017

TAJ MAHAL

• Description: the project demonstrates various visual effects of a taj mahal which can be controlled using keyboard keys.
• Technologies Used: Microsoft Visual Studio 2010.

FEB2018-MAY2018

DEVELOPED RESTAURANT MANAGEMENT APPLICATON

• Description: Developed to provide detailed description of Restaurant Management.It works with various food menus and enables the costumer to order food based on menus.
• Technologies Used: PHP, HTML, CSS, xamp control panel .

AUGUST2018-APRIL2019 

DEVELOPED A PERSONALIZED RESEARCHER RECOMMENDATION APPROACH IN ACEDEMIC CONTEXT USING MACHINE LEARNING TECHNIQUES.

Description: developed a personalized researcher recommendation system using machine learning techniques.

• The goal of this recommendation system is to predict user interests in academic context. Based on the user's demands and while taking into account their interests, this system can give them the information they need. A more thorough analysis of the data is required to provide better recommendations. In this project, we have implemented book or thesis paper(which are used in academic context) recommendation system using machine learning techniques. We have studied and compared different recommendation models and using the best model we have implemented this recommendation system for recommending book or thesis paper to the user. Machine learning is used in this recommendation system because it gives an entity the potential to learn artificially without explicit programming.
• Technologies Used: Application Server-Tomcat 6.0.
• Front End-HTML ,Java , Jsp. Database-Mysql 5.0.

FEB2019-APRIL2019

Developed Content Based Recommender System.

• Developed a Content-Based Recommender works by the data that we take from the user, either explicitly (rating) or implicitly (clicking on a link). By the data we created a user profile, which is then used to suggest to the user, as the user provides more input or take more actions on the recommendation, the system becomes more accurate.
• Technologies Used: Application Server-Tomcat 6.0.
• Front End-HTML ,Java , Jsp. Database-Mysql 5.0.
• Company: DataLore Labs.

BASICS OF IOT PROGRAMMING FROM ETHNOTECH ACADEMIC SOLUTIONS.

SKILL DEVELOPMENT TRAINING PROGRAM FROM SJB INSTITUTE OF TECHNOLOGY BANGALORE.