Machine Learning Data Science

Naveen Kumar Kavila Email: ******************@*****.***

Portfolio: https://www.linkedin.com/in/naveen-kumar-kavila-172394183/ Mobile: +1-813-***-**** Education

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University of South Florida Tampa, USA

Masters of Science - Business Analytics and Information Systems; GPA: 3.52/4.00 Aug 2022 - May 2024 Courses: Data Science, Analytical Methods for Business, Machine Learning, Databases, Project Management

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V. R. Siddhartha Engineering College Vijayawada, India Bachelor of Technology - Computer Science; GPA: 7.00/10 July 2016 - Sep 2020 Courses: Operating Systems, Data Structures, Analysis Of Algorithms, Artificial Intelligence, Networking, Databases Skills Summary

• Languages: Python, C++, R, JavaScript, SQL, PHP, JAVA

• Frameworks: Scikit, TensorFlow, Keras, Django, Flask, NodeJS

• Tools: MySQL, SQL server Management studio, SQLite, MongoDB

• Data Science Libraries: NumPy, pandas, Matplotlib, Scikit Learn, TensorFlow, keras

• Visualization Tools: Tableau, PowerBI, MS Excel, Seaborn, plotly

• Cloud Platforms: AWS, Azure

• Machine Learning: Regression, Classification, Clustering, Boosting, CNN, KNN, RNN, LSTM, MLP, NLP Experience

ICICI Bank(Client) Remote

Data Analyst(Full-time)— SQL, R, Python, Tableau, PowerBI Nov 2020-Feb 2022

• Leveraged data analysis to reduce credit risk by a percentage, resulting in substantial savings:

• Developed predictive models for forecasting financial trends, contributing to enhanced risk assessment:

• Produced interactive data visualizations and dashboards, improving data-driven decision-making.: Electronics Corporation of India Limited- ECIL(ECIT) Hyderabad Project (Intern) April 2019 - July 2019

• About Project: ”I worked in a team of four people on an Android project, ’A Real-Time Crime Records Management System for National Security Services,’ as part of the project requirements.” Projects

• Accident severity Prediction: ”Developed a machine learning project for nationwide accident severity prediction, with a focus on major U.S. cities. Compared KNN, Random Forest, Logistic Regression, and Decision Tree models, with the Random Forest model achieving the best accuracy. The best model’s accuracy score was achieved by Random Forest”

• Flexible Off-Campus Housing Locator: Our ’Flexible Off-Campus Housing Locator’ project leverages HTML, CSS, and JavaScript for a user-friendly front-end. Powered by Flask on the back end, it enables students to find off-campus accommodations near various universities. This scalable platform allows us to adapt to real-time situations by incorporating additional locations and institutions as needed.

• Exploring the Dynamics of Income Inequality and Economic Growth: In our data visualization project, we analyzed global income inequality and economic growth trends using datasets from the Global Consumption-Income Project, and the World Bank, we employed Tableau for analysis. Through interactive charts and maps, we observed a consistent pattern of increasing income inequality across countries, regardless of economic growth. This underscores the urgency of addressing inequality through policy measures.

• Real Estate Price Prediction Project using machine learning model: Developed a real estate price prediction website using machine learning, encompassing data preprocessing, model creation (sklearn linear regression), and Flask server deployment. The website, built with HTML, CSS, and JavaScript, enables users to input property details and obtain predicted prices.

Volunteer Experience

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Member at Club NSS

As an active NSS member at VRSEC, I’ve participated in various community service initiatives, fostering personal growth.

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