Vismaya Shivamogga Narayanamurthy

Organized and dependable candidate successful at managing multiple priorities with a positive attitude. Willingness to take on added responsibilities to meet team goals.

 Reliability Checking and Performance Analysis of stakeholder of ESCM  Using Machine Learning and Peri nets 

 November 2020 - August 2021 

• Studied different Bayesian approach and Petri Nets to design and develop a reliable model of E-SCM, ensuring optimum delivery time of the finished product.
• Coding and developing the program using Python, collecting data, Taking the initiative, and leading the team were the responsibilities.

 Baby Shop Management System  

 November 2019 - January 2020 

• The main objective of the project was based on Database management system used to manage articles in a baby shop
• Designed a DBMS-based solution allowing users to CRUD customer’s information using SQL and NetBeans

 Online Library Management System 

 October 2020 - January 2021 

• Designed a web application using PHP, HTML, JavaScript that permitted users to add, modify and delete the information

Exploratory Data Analysis on Google Playstore app

March 2023

• Chose the 'Google Play Store Apps' dataset from Kaggle, comprising 10841 records and 13 attributes. selected this dataset to gain insights into user preferences and application characteristics.
• Explored attributes and Conducted in-depth analysis to group apps by category, assess user ratings, review counts, installation counts, pricing models, and content visibility.
• Cleaned the data by addressing outliers and missing values, ensuring data consistency. Generated histograms for cleaned data to visualize key trends and patterns. This exploratory analysis laid the foundation for deeper project insights and conclusions about application performance and user preferences.

Analyzing "Covid-19 UK Dataset"

April 2023

• Analyzed a comprehensive COVID-19 dataset containing information on cases and vaccinations in the UK.
• Cleaned the data by addressing outliers and missing values, ensuring data consistency. Conducted histogram visualization for insights, enabling project progression.
• Formulated hypotheses around COVID-19 cases, including the correlation between cases and tests performed, as well as the age group most affected.

EDA on Awarded Contracts from Federal Data Procurement System(FDPS)

May 2023

• Cleaned the data by addressing outliers and missing values, ensuring data consistency. Conducted histogram visualization for insights, enabling project progression.
• The analysis of the FPDS data provides valuable insights into the distribution of awards in the federal procurement landscape, highlighting key geographical, categorical, and temporal patterns. These insights can inform decision-making processes for businesses seeking federal contracts and aid in understanding the procurement trends within specific departments and regions.

Participated in National Webinar on Cyber Security, JNN College of Engineering, Shivamogga