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AI OVERVIEW:
AI OVERVIEW:
This section contains my Artificial Intelligence learning journey, including applications, mini-projects, and certifications.
This section contains my Artificial Intelligence learning journey, including applications, mini-projects, and certifications.
AI PROJECTS:
AI PROJECTS:
1-MEMORAID
1-MEMORAID
Project Overview:
Memoraid is an AI-powered companion designed to assist people living with Alzheimer’s and their caregivers. Using multimodal input—including images, text, and voice—it provides personalized memory support, safety monitoring, and daily guidance. By combining advanced AI reasoning with intuitive interfaces, Memoraid improves patient independence while reducing caregiver stress.
Tools used:
Python – for backend logic and API integration
Machine Learning – to process natural language and generate intelligent responses
AI Model / Library – Pre-trained language model (via AI API) for text understanding and generation
Outcome:
Alzheimer’s patients face challenges with memory lapses, safety hazards, and managing daily routines. Caregivers often experience constant supervision pressure. Existing tools lack context-aware assistance that integrates environmental awareness with personalized guidance. Memoraid fills this gap using Gemini 3 Pro’s multimodal reasoning capabilities.
Memoraid enhances patient independence, reduces caregiver stress, and provides actionable safety alerts. It has tangible societal and household benefits, improving daily life and safety outcomes for both patients and caregivers .
App link: Memoraid
Youtube Description video: youtube
App Link:
2-ECO-SORT
2-ECO-SORT
Description:
Eco-Sort helps waste-management facility workers decide how to dispose of waste items on a conveyor belt.
The user uploads an image, and the app immediately classifies the waste into the correct category with a clear colored visual flag.
Tools Used:
Python – for backend logic and API integration
Machine Learning – to process natural language and generate intelligent responses
AI Model / Library – Pre-trained language model (via AI API) for text understanding and generation
Outcome:
Sorting waste on a fast-moving conveyor belt is error-prone, especially with contaminated, obscured, or hazardous items. Misclassification risks safety, the environment, and recycling efficiency. Only a GenAI system analyzing images for material type and contamination can provide instant, reliable, color-coded guidance to support safe and efficient waste management.
App Link:
3-Grammar Checker
3-Grammar Checker
Description:
Description:
The Grammar Checker app is an AI-based application that analyzes user-entered text and identifies grammatical errors. It provides corrected sentences and suggestions to help users improve their writing quality and language accuracy.
Tools Used:
Tools Used:
Python – for backend development and handling requests
Machine Learning – for detecting and correcting grammatical mistakes
Hugging Face AI Model / Library – pre-trained language model used for grammar correction and text processing
Outcome
Outcome
The application helps users write grammatically correct text by automatically detecting errors and suggesting improvements. Through this project, I learned how to use a Hugging Face pre-trained model, integrate it into an application, and apply machine learning for real-world language tasks.
CERTIFICATES:
CERTIFICATES:
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