Data Engineering Projects

Gen AI Projects

An AI-powered tool designed to convert audio recordings and live speech into accurate text transcriptions. The system supports both pre-recorded audio uploads and real-time speech input through a microphone, ensuring seamless and efficient transcription. Leveraging advanced natural language processing (NLP) and speech recognition algorithms, the tool is capable of handling diverse accents, languages, and audio qualities.

Speech To Text Recognition

Knowledge Gap Solution

A generative AI tool designed to bridge knowledge gaps for new employees, particularly in sales. This solution ensures that new hires have comprehensive knowledge of company history, legacy products, and improvements, helping them connect with customers and avoid missed opportunities. By addressing these gaps early, the tool aims to reduce revenue loss and boost customer satisfaction.

A personalized AI-driven assistant that provides mental health support based on user inputs. The system offers real-time chat responses and, when needed, suggests psychiatrists nearby using Google Maps integration. Built as a web app using Streamlit, this tool is designed to assist users in managing their mental well-being with relevant advice and local resources.

Mental Health Assistant

Machine Learning Projects

An ML-based solution designed to predict used car prices based on various features such as odometer, mileage, model, and year. The project involved extensive data cleaning and preprocessing, followed by the application of regression models like Linear Regression, Random Forest, and XGBoost. The best-performing model was integrated into a Streamlit web app, enabling users to input car specifications and instantly receive price predictions.

Used Car Price Prediction

Amazon Review Sentiment Analysis

Leveraging natural language processing (NLP) techniques, this project classified Amazon product reviews as either positive or negative. The model was trained on a large dataset of reviews to accurately understand and predict customer sentiments, offering valuable insights into user feedback. The results help businesses gauge public opinion on products quickly and efficiently.

Breast Cancer Prediction

Developed a classification model that predicts whether breast cancer is benign or malignant using patient data. By analyzing features like cell size, shape, and distribution, the model aids in early detection and diagnosis. The project applied advanced classification algorithms to ensure high accuracy, contributing to more informed medical decisions.

Covid-19 Detection

Built a machine learning model to detect COVID-19 cases using healthcare data. The model was trained to identify key symptoms and patterns associated with the virus, providing a reliable tool for early diagnosis and helping healthcare providers make quicker decisions during the pandemic.

Data Analysis Projects

Conducted a comprehensive data analysis to explore the impact of COVID-19 on employee layoffs across various industries and regions. This project examined the relationship between economic factors and layoff trends using statistical techniques. The findings were presented through insightful visualizations created with Matplotlib, Seaborn, and Plotly, providing a clear picture of the pandemic’s effect on employment.

Employee Layoff since Covid-19

IPL Player Performance Analysis

Analyzed the performance of players and auction dynamics in the Indian Premier League (IPL). This project integrated data from multiple sources, including player statistics, auction data, and team performance. Using Python and data visualization libraries, the analysis identified key contributors and trends, helping to better understand player metrics and team strategies.