Kavya Lalbahadur Joshi

My journey into the world of data analytics and machine learning began with a simple yet profound curiosity about how technology shapes our daily lives. Growing up in an era where data-driven decisions transformed industries, I became captivated by the potential of harnessing data to solve complex problems. This passion drove me to delve deeper into the fields of data science and artificial intelligence.


I completed my Bachelor's in Computer Applications followed by a Post Graduate Diploma in Data Science and Artificial Intelligence. Currently, I’m pursuing my Masters in Computer Science at North Carolina State University.


My experience includes internships at TCS iON and Verzeo. At TCS ion, I worked as an Artificial Intelligence Intern, where I utilized advanced algorithms combining rule-based and deep learning approaches to accurately predict emotions expressed in English text, achieving a remarkable accuracy of 98%. At Verzeo, I worked as a Machine Learning Intern. I developed a machine learning model utilizing a support vector classifier and count vectorizer on a proprietary dataset to predict startup review sentiment, achieving 94% accuracy and optimizing decision-making processes.


Outside of my academic pursuits, I am an avid reader with a particular love for contemporary fiction and mystery thrillers. Some of my favorite authors include J.K. Rowling, Dan Brown, and Agatha Christie. I also have a passion for painting and am an amateur guitarist. Additionally, I am a trained Bharatnatyam dancer, having completed my Bachelor's degree in this classical art form.


I am currently seeking full time opportunities in the dynamic fields of data science and artificial intelligence. If you are looking for a dedicated and passionate individual with a strong background in data analytics, machine learning, and database management, I would love to connect!

Education

North Carolina State University ( Aug 2023 - May 2025)
Masters in Computer Science

Relevant Coursework: Software Engineering, Design and Analysis of Algorithms, Database Management System and Concepts

Savitribai Phule Pune University ( Aug 2022 - Aug 2023)
Post Graduate Diploma in Data Science and Artificial Intelligence

Relevant Coursework: Natural Language Processing, Machine Learning, Statistics

Savitribai Phule Pune University ( July 2019 - July 2022)
Bachelors in Computer Applications

Relevant Coursework: Android Programming, Cloud Computing, Management Information Systems, Operating Systems

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Work Experience

TCS ion, Pune, India
Artificial Intelligence Intern
01/2022 – 03/2022
• Utilized advanced algorithms, combining rule-based and deep learning approaches, to accurately predict emotions expressed in English text, achieving a remarkable accuracy of 98%.
• Refined and optimized machine learning models based on insights gathered from focus groups, resulting in a significant 9.2% improvement in the F1 score.
• Integrated these models into operational ML pipelines and documented the model development process for future reference.

Verzeo, Pune, India
Machine Learning Intern
11/2021 – 01/2022
• Developed a machine learning model utilizing a support vector classifier and count vectorize on a proprietary dataset to predict startup review sentiment, achieving 94% accuracy and optimizing decision-making processes.
• Automated advanced data pre-processing strategies, significantly minimizing manual intervention and enhancing data quality for precise model training and also performed regression analysis to predict the profit of 50 start-ups.
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My Projects

Machine Translation
01/2022 – 03/2022
• Developed and compared two models, LSTM and CNN, for translating English text into Hindi using a dataset of 83,053 samples.
• Implemented data preprocessing and tokenization techniques to prepare text data for training.
• Convolutional Neural Networks outperformed Long Short-Term Memory networks in this text-based translation task.


Slash
10/2023 – 12/2023
• Developed a web API framework that allows to scrape the most popular e-commerce websites to get the best deals on the searched items across e-commerce websites like Walmart, Target, Best Buy, and EBay. • Managed and organized essential website data in a PostgreSQL database. • Integrated this data with FAST API to build a user-friendly web framework.


Netflix User Analysis
08/2023 – 10/2023
• Lead a team of four to predict the ratings given by users for a particular movie using collaborative filtering with the help of K Nearest Neighbors, K-Means, Linear Regression, and Graph Neural Networks to classify data based on genre, leveraging a dataset encompassing over 100 million movie ratings from 480,000 users.
• Evaluated model performance using Root Mean Square Error (RMSE) and accuracy, with K Nearest Neighbors (KNN) emerging as the top-performing model, demonstrating superior predictive capability compared to other algorithms.


SimplyClip
10/2023 – 12/2023
• Implemented and designed a Google Chrome extension that makes life easier for students and power users • Tech stack used: HTML, CSS, JavaScript, Python, Node.js, NPM


Market Segmentation
05/2023 – 07/2023
• Designed a Streamlit Application that harnesses the power of the K-means clustering technique to efficiently categorize credit card holders based on their individual details.
• Performed training and testing using two different algorithms like Decision Tree and Random Forest, further deploying the Random Forest model on Streamlit application as it achieved an accuracy of 98%.
• Visualized the reports using Power Bi.


Kids Vaccination App
03/2023 – 04/2022
• Created an Android Application in Android Studio to keep track of vaccination schedules for children up to 15 years of age. • Maintained a SQLite database to store crucial information such as user details and vaccination dates, ensuring efficient tracking of both actual and expected vaccination dates.

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