CardWise AI is a personal-finance assistant focused on helping users evaluate credit-card options, align card selection with financial goals, and understand spending behavior through AI-generated summaries. Focus Areas Personalized card recommendations based on user goals and constraints. Goal-aware planning support for safer and more structured decision-making. Natural-language insights to explain spending patterns in simple terms.
Overview DocCompass is a local-first document discovery system built to find personal files by meaning, not only by filename. It is designed for natural requests like: “my marksheets” “visa related documents” “intro to psychology notes” The project searches local directories, extracts text from multiple file formats, builds a reusable index, creates a structured query plan, and ranks results by relevance with transparent scoring. Repository: github.com/singhaditya8499/DocCompass Problem Statement Traditional local file search is often fragile because it depends heavily on exact filenames and folder memory. In real usage, users usually remember intent and partial context, not exact paths. DocCompass addresses this by combining: ...
Face Recognition System is a practical computer-vision pipeline that covers full lifecycle stages: data capture, model training, and live identity recognition. Highlights Captures and curates face samples for training. Trains a recognition model from collected data. Runs real-time identification on live video streams.
Hand Game is a real-time interaction project where hand gestures become game controls through computer-vision based finger and contour detection. Highlights Uses webcam input for gesture capture and detection. Converts hand movements into gameplay actions. Demonstrates low-latency vision-to-input integration.
LeetCode Rank Finder is a lightweight automation utility that solves the practical challenge of locating a specific contestant quickly in large contest ranking tables. Highlights Fetches and parses contest ranking data. Searches standings by username and returns rank details. Reduces manual effort during contest analysis.
Markov Chain Basic is an exploratory NLP project that uses Markov transitions to generate text and study long-run behavior in probabilistic sequence models. Highlights Builds transition maps from input corpora. Generates synthetic text using stochastic state transitions. Serves as an intuition-first bridge into probabilistic NLP.