Hey, my name is
Megha Gupta
Data Scientist/Full-stack Developer
About me
I am an experienced Data Science professional with a master’s degree and more than 4+ years of experience as a Full-Stack Software Developer. I have successfully worked on real-life data science projects, delivering data-driven solutions and utilizing my technical skills to extract valuable insights. I am dedicated to continuous learning and eager to find opportunities to make a meaningful impact in the field of data science and analytics.
Education & Experience
2013-2017
University of Mumbai, India
Bachelors in Computer Science
2021-2023
Rochester Institute of Technology
Masters in Data Science
Testimonials
Megha is a quick learner and she always tries to keep herself abreast with latest technologies. She takes full ownership and accountability of her work which is of paramount importance in any professional. She has always been an important asset to the projects. She is dedicated ,self motivated and always tries to complete her task in the best possible way known to her. Her problem solving skills and technical knowledge further strengthens her competency. Also, the positive attitude towards work inspires and motivates people to be like her.
Megha proved to be crucial to the team and contributed significantly to the development of the company. She consistently demonstrated a solid work ethic, and a dedication to success. Overall Megha is a detail-oriented team player. On account of her mature approach to her responsibilities, I often thought of Megha as a professional I could always rely upon to get the job done. She consistently demonstrated a solid work ethic, and a dedication to success.
Megha is a fantastic resource and a very good Team player. She has a very good Analytical skills and technically strong. Megha has a very good work ethic and she is an asset to the team.
Projects
Striking a balance between software performance and regular testing is challenging due to limited resources, often resulting in neglected performance regression checks. Although these regressions are infrequent, their potential impact necessitates substantial commit reversions. To tackle this, this machine learning initiative employs binary classification algorithms with resampling techniques to predict the need for performance regression tests when making commit changes.
https://github.com/meghagupta08/Minimizing-performance-regression
A classifier designed to identify different types of Distributed Denial of Service (DDoS) attacks utilizing a range of machine learning techniques. The primary goal of this classifier is to accurately detect and differentiate between various forms of DDoS attacks. The classifier’s performance was evaluated using cross-validation, achieving an accuracy rate of 98%.
A statistical analysis involves a comprehensive investigation into the various statistical factors that impact the academic performance of students. This project could encompass a wide range of educational contexts, from primary and secondary education to higher education institutions. The primary goal of the project was to identify and understand the statistical variables that contribute to student success or challenges.JMP (A statistical analysis tool) was used to perform hypothesis testing, ANOVA test and employed other statistical methods to determine the affect various parameters on academic performance of students.
https://github.com/meghagupta08/Analysis-of-statistical-factors-affecting-students-performance
This project involves employing computer vision techniques to monitor the growth of silicon crystals and detect the presence of facets, which are flat sides on the crystals. The primary objective is to develop a real-time prediction system that can identify facets as they form during crystal growth, thereby impacting the quality and cost-effectiveness of the process. Through the utilization of advanced computer vision methods, this initiative aims to optimize the production of silicon crystals by enhancing facet detection and, consequently, improving overall economic efficiency.
https://github.com/meghagupta08/Optimizing-Silicon-Crystal-Growth
The goal of this project is to develop a Document Question Answering app powered by Large Language Models (LLMs), such as Falcon-7B and Dolly-v2-3B, utilizing the LangChain platform and the ChromaDB vector database. By leveraging the capabilities of LLMs, this app aims to provide users with accurate and comprehensive answers to their questions within a given document corpus
https://github.com/meghagupta08/llm-document-question-answering
hackathons
Fresh Check
A smart fridge computer-vision based application, that helps to keep your fridge in check. Tells you which food items are expiring.
Eventify – U
Eventify-U was to create a platform that would connect university students with events that match their interests, providing a personalized experience that would enhance their college experience.
