About Me
As a data science student, I bring hands-on experience through impactful projects in predictive modeling and data analysis. Proficient in Python I've translated theoretical knowledge into practical solutions. My passion lies in uncovering insights from diverse datasets, showcasing my commitment to real-world problem-solving. Eager to contribute my skills and continue evolving in the dynamic field of data science. Let's connect and explore the exciting narratives within data through my project portfolio!
Goal
The goal is to turn data into information,
and infromation into insight
Skills
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Python
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Machine learning
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Deep learning
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Computer Vision
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Data analysis
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Data Science
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Large language models
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Natural language processing
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DataBases
Education
I am in the final year of my Bachelor's degree in Artificial Intelligence and Data Science from Vignan Institute of Information Technology, maintaining a CGPA of 9.31. During my studies, I have gained both theoretical and practical knowledge in machine learning algorithms, NLP and data visualization techniques.
Experience
I have experience as a Data Science and AI Intern at Innomatics Research Labs, where I developed a RAG system using LangChain, led a sentiment analysis project with MLOps tools, and optimized pizza store operations through data analysis. Additionally, I interned as a Machine Learning and Cloud Intern at Skill Vertex, working on the Diamond price prediction project, automating pipelines, and deploying on AWS cloud. I also served as a Campus Ambassador for Geeks for Geeks, developing leadership and event management skills.
Interests
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Statistics
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Linear algebra
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Calculus
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Artificial intelligence
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Automation
Experience and Projects
10+
Projects Completed
3
Internships
5+
Certifications
Experience
Data Science and AI Intern
During my tenure as a Data Science and AI intern, I have been involved in several projects that have allowed me to develop and refine my skills in areas such as machine learning, natural processing, and data analysis Specifically, I was responsible for creating an RAG bot that utilized LLM's and external data to enhance accuracy and user experience. Additionally, I spearheaded a sentiment analysis project that leveraged MLOps tools for seamless model development and deployment. Lastly, I leveraged data analysis to optimize a pizza store's operations by improving delivery routes, reducing times, and boosting revenue.
SWE Fellow
Throughout my tenure as a Software Engineering Fellow, I had the privilege of contributing a variety of AI-related initiatives and engaging in multiple hackathons. These experiences enabled me to refine my technical proficiencies and acquire invaluable insights into the realm of software development. I am eager to leverage this knowledge and expertise in any future I undertake.
Cloud and ML Intern
I had a great experience during my ML and Cloud internship, where I was able to contribute to diverse projects, including the Diamond price prediction project. I built pipelines for seamless task automation and led the deployment of the project on AWS, which helped me enhance my cloud computing proficiency. Overall, it was a valuable learning opportunity that has helped me grow both personally and professionally.
Projects
deployed
on
Projects
Sentiment Analysis
​This project involved developing a sentiment analysis model to classify text data into positive and negative categories. The implementation utilized natural language processing techniques for text preprocessing and feature extraction. Automated pipelines were established using MLflow for experiment tracking and Prefect for automating the training process to ensure consistent model updates. Additionally, a user interface was created using Streamlit to provide an interactive platform for users to explore and analyze sentiment results.
Customer Support Chatbot
This project involves an innovative chatbot designed to enhance user interaction. The chatbot allows users to interact using their microphone for seamless audio input and supports audio file uploads for added flexibility. It processes audio input and provides responses in text form, ensuring an efficient conversation experience. The implementation leverages Hugging Face open-source models for natural language processing and features a user-friendly interface built with Gradio, making interactions simple and intuitive.
Attention Bot
The RAG (Retrieval-Augmented Generation) application is an advanced AI tool designed to answer queries based on the 'Attention is All You Need' research paper. It utilizes the Chroma Vector Database to store and access curated knowledge, Cohere Platform and LangChain for text embeddings and context retrieval, and Google's generative model for generating accurate responses. The application features a streamlined and intuitive chatbot interface built with Streamlit, providing an accessible and user-friendly experience for interacting with the model.
Real-time hand gesture recognition system that controls system volume. 🎵💻"
This project involves a Python script that combines MediaPipe and OpenCV to create a real-time hand gesture recognition system for controlling system volume. It addresses the business problem of providing a touchless, intuitive interface for volume control, which is particularly useful in scenarios where physical contact with devices is inconvenient or unsanitary. The script uses MediaPipe to accurately track the movements of the thumb and pointer fingers, dynamically adjusting the volume based on the distance between them. The pycaw library is integrated to interface directly with the system's audio controls, allowing for precise volume adjustments through hand gestures
Movie Recommender System
This project involves a content-based recommender system designed to suggest movies based on user input. By analyzing the features and attributes of movies, the system recommends similar movies that match the characteristics of the provided input movie.
Diamond Price Predictor
​This project involves a machine learning model for predicting diamond prices based on various characteristics. To streamline the workflow, I developed pipelines that automate data preprocessing and feature engineering. Additionally, I integrated MLOps tools such as MLflow for experiment tracking, Airflow for workflow automation, and DVC for version control, enabling continuous monitoring and management of the project. This setup ensures efficient and consistent model development, deployment, and maintenance.
Universal Translator
In the Universal Translator project, I have developed an application that can translate the text entered by the user into any language of their choice. This project was accomplished with the help of LangChain, ChatGPT API and Streamlit.
Forest Fire Predictor
For my Forest Fire Predictor project, I built a machine learning model that can forecast the likelihood of a forest fire based on various weather conditions such as temperature and humidity. Additionally, I created a user-friendly front-end application with Streamlit to allow easy interaction with the program.
Automated Taxi Service
In the project for an Automated Taxi Service, I trained a Reinforcement Learning agent with a Q-learning algorithm. The agent is designed to pick up customers and take them to their desired destination.
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Lunar Lander
In my Lunar Lander project, I trained an RL agent to land the spaceship accurately at the given landmark without any discrepancies.
Frozen Lake
In the Frozen Lake project, I trained a Reinforcement Learning agent using Q-learning algorithm to navigate the lake and reach the destination without falling into the water.
University Admission Predictor
In the project for University Admission Predictor, I have built an ML model that predicts the chance of getting admission into a university for masters based on exam scores such as GMAT, GRE, etc.
