Engineered a comprehensive social media platform functioning seamlessly across both web and mobile environments.

Utilized Capacitor JS [a cross-platform native runtime that allows web applications to run natively on mobile devices] to bridge the web application architecture into a native APK [Android Package Kit, the file format used by the Android operating system for the distribution and installation of mobile apps].

Implemented a Split-Query Search Engine [a database design pattern that runs entirely separate SQL queries to decouple distinct data types, merging them into a single formatted JSON array] to drastically reduce query clutter and improve data retrieval speed.

Deployed a Deep-Link Glow Engine [a custom routing system that mathematically reconstructs thread hierarchy, smoothly scrolls the target component into view, and triggers CSS animations] to handle complex cross-platform user navigation.

Integrated a robust Mobile Notification Engine utilizing Firebase Cloud Messaging [a cross-platform messaging solution that allows developers to reliably send messages and notifications] to route foreground and background taps directly to specific application states.

Developed a Supervised Regression [a type of machine learning where the model learns from a dataset that includes both the input features and the correct output answer] model to accurately forecast real estate values.

Constructed a robust Data Preprocessing Pipeline utilizing pandas [a software library written for data manipulation and analysis] and scikit-learn [a robust machine learning library] to handle missing numerical values via Median Imputation and categorically scale features through Standardization.

Evaluated algorithmic efficacy by comparing Baseline Ordinary Least Squares models against advanced Random Forest Regressors [an ensemble learning method that constructs a multitude of decision trees during training to improve accuracy and control overfitting].

Deployed the serialized model into a live production environment utilizing Streamlit [an open-source app framework that turns Python scripts into interactive web applications], providing users with dynamic input Widgets [graphical control elements] to execute live Inference.