MineVidya is an AI-powered knowledge assistant designed specifically for the Indian mining industry. It combines Retrieval-Augmented Generation (RAG) with hybrid search (semantic + keyword retrieval) to provide reliable, context-aware answers from mining regulations, DGMS circulars, accident investigation reports, and technical reference documents.
A comprehensive platform for automated evaluation of AI agent responses using multi-metric analysis, built with React TypeScript frontend and Python backend with machine learning capabilities.
CrisisWatchAI monitors Reddit mental health posts in real time to detect at‑risk users via risk classification, sentiment analysis, user tracking, and geolocation. Insights feed an interactive dashboard for professionals to enable timely outreach and interventions.
CrisisWatch AI monitors Reddit mental health posts in real time to detect at‑risk users via risk classification, sentiment analysis, user tracking, and geolocation. Insights feed an interactive dashboard for professionals to enable timely outreach and interventions.
MedSnap is an AI-powered tool for medical students and researchers to quickly process medical literature. It can: Skim medical abstracts into structured sections. Summarize research papers, abstracts, and notes. Provide real-time medical news with summaries and SEO details.
ProcessMapper AI is an AI-driven tool that reads SOP documents and automatically turns them into visual process maps, highlighting key steps, risks, and controls so organizations can understand, improve, and document their workflows more easily.
⚡ Automatically decrypt encryptions without knowing the key or cipher, decode encodings, and crack hashes ⚡
ElyxCopilot is a web app that visualizes Joseph Martinez’s 8‑month health journey in one place, combining his profile, chats, biomarkers, and timeline to make progress and care decisions easy to understand.
This project demonstrates text classification using Hugging Face's transformers and datasets libraries.
This project is part of the Finalytics Course: Data Science with Python and aims to predict client subscription to term deposits while analyzing factors that influence success. It combines Python-based data analysis and a PowerPoint presentation for insights.
A deep learning-based Bitcoin price prediction project that uses LSTMs, CNNs, and N-BEATS models for time series forecasting. The project includes: ✅ Data preprocessing and visualization ✅ Multiple deep learning models (LSTM, CNN, Dense, N-BEATS) ✅ Multivariate modeling and ensembling ✅ Future price prediction with trained models
This project uses Reinforcement Learning (RL) to train an AI agent to land a spacecraft in the OpenAI Gym Lunar Lander environment. The model leverages Deep Q-Networks (DQN) and other deep learning-based RL techniques for optimal landing strategies. 🔹 Key Concepts: Reinforcement Learning, Q-learning, Policy Optimization
"This project classifies IMDB movie reviews as positive or negative using machine learning. The dataset consists of 10,000 reviews and is split into training and testing sets. With thorough preprocessing and a robust classifier, we achieved an accuracy of 87.42%."