Nayil Ahmed Siddique

Health Care Diabetes Prediction Model | Data Science Capstone Project Engineered a Linear Regression model to predict mortgage expenses across U.S. regions, informed by family income and rental data. Performed deep Exploratory Data Analysis (EDA) for debt, population, and income trends, utilizing geo-maps, box plots, and heat maps. Created a dynamic Tableau dashboard to display real estate trends, debt distributions, and mortgage analytics for strategic insights. Real Estate Analysis for Mortgage Banking | Data Science Capstone Project Engineered a predictive model for diabetes diagnosis using key health indicators from NIDDK data, including BMI and glucose levels. Implemented advanced data preprocessing and normalization, ensuring data integrity and addressing missing values. Applied various machine learning techniques like KNN for accurate predictions, with an emphasis on evaluation metrics like ROC. Retail Customer Segmentation & Insights | Data Science Capstone Project Implemented RFM analysis to segment retail customers, identifying valuable segments based on recency, frequency, and monetary metrics. Developed and evaluated a k-means clustering model to group customers, revealing distinct patterns and insights for targeted strategies. Crafted a Tableau dashboard for visualization of customer’s spending pattern, top products & order trends, supporting business strategies.

Fruit Quality Detection | B.E final year Major Project | GitHub Nov 2022 - Mar 2023 Actively engaged remotely on lip to speech synthesis project, working with a team of dedicated researchers & engineers. Developed & implemented advanced machine learning algorithms & cutting-edge speech synthesis models for the project. Contributed to the seamless delivery of the project, meeting requirements, strategic objectives and ambitious timelines. Lip 2 Speech Synthesis | Varcons Technology Internship Project | GitHub Sep 2022 - Nov 2022 Engineered a real-time fruit quality detection system using smartphone cameras integrated with deep learning algorithms. Developed a user-friendly web interface for instant assessment, revolutionizing fruit quality evaluation in various sectors. Conducted rigorous testing to ensure the system's reliability and accuracy, ensuring consistent and dependable results.