M

Machine Learning

The AI-Driven Crop Disease Prediction and Management System is an intelligent agricultural platform designed to help farmers detect, analyze, and manage crop diseases at an early stage using artificial intelligence and computer vision.

The system allows users to upload images of crops or capture them in real time through a camera. Using advanced deep learning and image processing techniques, the model identifies diseases affecting leaves, stems, or fruits and provides accurate predictions along with confidence scores.

Beyond detection, the system goes further by offering actionable agricultural insights, including treatment recommendations, preventive measures, pesticide suggestions, and crop care guidance. This transforms the application from a simple detection tool into a complete decision-support system for farmers.

The platform can also integrate weather data, soil conditions, and historical crop patterns to improve prediction accuracy and provide context-aware suggestions. A user-friendly dashboard ensures that farmers and agricultural experts can easily interpret results without technical complexity.

Key Features: 🌿 Real-time crop disease detection using image input 🧠 AI-based classification of plant diseases 📊 Confidence score and severity analysis 💊 Treatment and prevention recommendations 🌦️ Optional integration with weather and soil data 📱 Simple and accessible web/mobile interface 📈 Analytics dashboard for crop health monitoring Objective:

To empower farmers with early disease detection and smart recommendations, reducing crop loss, increasing yield, and enabling data-driven agriculture.

Local-First Document Q&A with RAG using Ollama — Find-Retrieve-Answer pattern

SafeRoute AI is a machine-learning-powered road safety platform that predicts accident blackspots, analyzes route risk, and recommends safer travel routes using FastAPI, Next.js, SQLite, and XGBoost.

Attendance Tracker is a digital solution designed to automate and simplify attendance management for organizations, educational institutions, and teams. The system enables users to record, monitor, and analyze attendance data efficiently while reducing manual effort and errors associated with traditional attendance registers.

The application provides features such as employee/student check-in and check-out, attendance history, leave management, real-time attendance monitoring, and report generation. Users can mark attendance through various methods, including manual entry, QR code scanning, GPS location verification, or facial recognition, depending on the organization's requirements.

Administrators and managers can access dashboards that display attendance statistics, late arrivals, absences, and workforce availability in real time. The system also supports automated notifications, attendance correction requests, and integration with payroll or academic management systems.

Advanced versions of the Attendance Tracker may include AI-powered analytics, geofencing, anomaly detection, and predictive insights to help organizations improve attendance compliance and operational efficiency.

Smart Cab Finder is an AI-powered ride comparison platform that helps users compare fares, estimated arrival times, and ride options across multiple cab providers. The application includes an intelligent AI assistant for ride recommendations, supports Bring Your Own Key (BYOK) integrations, and is designed to support local AI inference through Ollama. To improve accessibility, the platform provides multilingual support in English, Hindi, and Telugu. Built using Python and Flask, the project follows secure development practices with automated testing, CI/CD pipelines, security scanning, and compliance-driven documentation.

Bank Customer Churn Analysis is a data analytics and machine learning project designed to identify customers who are likely to leave a bank's services. Customer churn is a major challenge for banks, as retaining existing customers is more cost-effective than acquiring new ones. This project analyzes customer demographics, account details, transaction behavior, and banking activity to uncover patterns that contribute to customer attrition.

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AI Government Scheme Recommender helps users find eligible government schemes using Streamlit and Python.

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Farmin.AI is an AI-powered assistant designed to help farmers with intelligent crop advisory, disease detection using image analysis, and farm record management. Built with a user-friendly Streamlit interface, it simplifies agricultural decision-making using modern technologies like machine learning, natural language processing, and data-driven insights. Ideal for small to medium-scale farmers aiming to boost productivity and sustainability.

LokKala is a lightweight, open-source Streamlit web app for collecting folk stories, proverbs, and meme captions in Indian languages. It works offline and contributes to building culturally diverse AI datasets for the viswam.ai mission.

MindMate is an open-source AI-powered assistant designed to support mental wellness through empathetic and non-judgmental conversations. Built on Hugging Face Chat Assistants with meta-llama/Llama-3-70B-Instruct as the base model, it provides mindfulness suggestions, stress management tips, and gentle motivational prompts. The goal of MindMate is to create a safe, conversational space where users can find support for stress, anxiety, and emotional challenges, while maintaining privacy and open-source transparency.

BakBak-Bot

BakBak-Bot is an advanced conversational AI assistant built for linguistic research, machine learning training, and digital archiving purposes. The bot leverages natural language processing (NLP) to understand and respond to user queries in multiple languages, making it an ideal tool for researchers, educators, and developers working on language technologies.

Key Features Multi-language Support: Communicate in various languages Intelligent Conversations: Context-aware responses using NLP Research-Oriented: Designed for linguistic analysis and data collection Digital Archiving: Store and retrieve conversation data efficiently Extensible Architecture: Easy to customize and extend functionality

Telugu Farmer Assistant is a free, AI-powered platform for farmers in Telangana and Andhra Pradesh. It provides crop disease diagnosis, soil-based crop planning, and real-time weather updates — all in Telugu language, with an offline-first design for accessibility.

AI/ML-based tool that predicts the likelihood of diabetes using medical parameters such as glucose, BMI, age, and blood pressure.

AI-powered platform for collecting and analyzing multilingual cultural narratives from global communities, built with Streamlit and Python.

A family recipe sharing app built with Python for managing and sharing recipes across family members.

A cryptocurrency price prediction system using LSTM neural networks. Groups coins by market dynamics and forecasts future prices for investors and traders.

🎬 Telugu Movie Review Sentiment Analysis using Machine Learning and Flask. Classifies Telugu movie reviews into Positive, Negative, or Neutral. Built as part of the Swecha Internship program for Telugu NLP.

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