Advanced AI Model for Disease Prediction

Developed an AI model for predicting genetic predisposition to diseases using genomic data. Applied deep learning techniques like CNNs and Autoencoders, achieving an accuracy of 92%. The model was optimized to reduce training time by 20%.

Technologies: Python, TensorFlow, Keras, CNN, Autoencoders, NumPy, Pandas.

This model leverages large-scale genomic data to identify disease risk markers, contributing to personalized healthcare advancements.

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Self-Supervised Learning for Image Captioning

Developed a self-supervised model that generates descriptive captions for images. This technology was used to assist visually impaired individuals by providing real-time contextual captions.

Technologies: Python, TensorFlow, CNN, LSTM, NLP.

The system intelligently interprets images using advanced natural language processing and machine learning techniques to generate human-like captions.

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Genre Classifier for Music Streaming Platforms

Built a machine learning model to classify music genres based on audio features. The model improved music recommendation accuracy by 20%, enhancing user experience on streaming platforms.

Technologies: Python, Scikit-learn, KNN, Decision Trees.

This project helped music platforms tailor their suggestions to users' tastes by effectively categorizing music into distinct genres based on complex sound features.

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AI-Powered Financial Forecasting Model

Developed a predictive model for financial forecasting using machine learning algorithms. It implemented time-series analysis to predict stock market trends with an 18% improvement in forecast accuracy.

Technologies: Python, Scikit-learn, ARIMA.

The model's robust analysis of historical financial data assists in making informed investment decisions.

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Smart Personal Assistant Chatbot

Created a smart personal assistant chatbot capable of handling user queries and performing tasks like setting reminders, fetching weather updates, and providing information on various topics. The chatbot utilizes NLP for better understanding user intents.

Built using Python with libraries such as Rasa and SpaCy, the chatbot incorporates machine learning algorithms for continual learning and improvement based on user interactions.

This project enhances user experience by providing immediate assistance and information, promoting productivity and efficiency in daily tasks.

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Crop Health Detection System

Developed a mobile application that detects crop diseases using image recognition, achieving 85% accuracy in real-time predictions. Integrated machine learning models to identify patterns in crop health data.

Technologies: Python, OpenCV, Android Studio.

This app provides a crucial tool for farmers, helping to reduce crop damage by enabling early disease detection.

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Agri-Fintech Loan Management App

Developed a mobile application to simplify the loan process for farmers, integrating Google Maps for location-based credit eligibility checks. The app helps banks and financial institutions manage loan distribution efficiently by identifying farm locations and soil conditions.

Technologies: Android Studio, Firebase, Google Maps API, Java, SQLite.

The app offers a streamlined experience for farmers applying for loans, reducing paperwork and improving transparency in the agrifintech space.

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Fitness Tracker App

Developed as part of an advanced Android course, this app tracks user fitness activities using sensors and GPS. Features include step counting, distance tracking, and route mapping on Google Maps.

Implemented user goals, progress charts, and social sharing functionalities.

Technologies: Android Studio, Kotlin, Google Fit API, Google Maps API, MPAndroidChart library.

The app promotes healthy living by enabling users to monitor and share their fitness journey.

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Restaurant Finder App

Built an app that helps users find nearby restaurants using Google Maps and Places API. Includes features like search filters, user reviews, and ratings.

Integrated real-time navigation to guide users to selected locations.

Technologies: Android Studio, Java, Google Maps API, Google Places API, Retrofit.

This project enhances user convenience by simplifying the search for dining options.

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E-commerce Web Application

Built a scalable e-commerce platform for small businesses with user authentication, real-time inventory management, and secure payment integration. Implemented best practices for security and performance optimization.

Technologies: React.js, Node.js, Express.js, MongoDB.

This project empowers small businesses with a reliable online presence, offering seamless user experiences and secure transactions.

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Automated News Website – Legitcon

Developed an automated news website using SEO techniques, allowing users to access top news articles. Successfully indexed on major search engines, attracting significant traffic.

Technologies: Python, Django, SEO Tools, MySQL.

This project streamlined the content aggregation process, providing users with real-time, relevant news updates.

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Online Marketplace with AI-driven Recommendations

Developed an online marketplace that uses AI to offer personalized product recommendations based on user behavior. Integrated payment gateways, user authentication, and dynamic inventory management.

Technologies: React.js, Node.js, Express.js, MongoDB, TensorFlow.

The AI-driven recommendation system improved user retention and increased sales by providing personalized shopping experiences.

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SaaS-based Task Management Tool

Developed a SaaS task management tool for teams to collaborate and track their projects. Features include drag-and-drop task boards, team chat, and file sharing, with a responsive UI for both web and mobile users.

Technologies: React.js, Firebase, Node.js, Stripe API, Docker.

This tool allows teams to stay organized and productive by providing an intuitive and interactive project management interface.

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Progressive Web App for Event Management

Developed a Progressive Web App (PWA) that allows users to organize, track, and manage events seamlessly across devices. The app includes features like real-time notifications, attendee tracking, and integration with calendar apps for event reminders.

Technologies: React.js, Node.js, Service Workers, Web Push API, MongoDB.

The PWA offers an offline-first experience, making it reliable even without a stable internet connection, and enhancing user engagement through real-time updates.

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E-learning Platform with Real-time Collaboration

Developed an e-learning platform that supports live sessions, real-time chat, and collaborative document editing. Students can join virtual classrooms and work on assignments together with integrated video conferencing and document collaboration tools.

Technologies: React.js, WebRTC, Firebase, Node.js, MongoDB.

This platform enhances remote learning by providing interactive features and real-time collaboration, fostering a more engaging learning environment.

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