__projects__
Gokap Inno Tech
Created a platform using Django and its REST framework for freelancers and clients to connect, post jobs, and apply for projects. Designed a sleek landing page with Figma and ensured secure API interactions with JSON Web Tokens. Deployed on Render Cloud for seamless user experience.
Tags: Django Figma JWT Neon Render Rest Framework
NGO Website Development
Designed and developed a user-friendly website for an NGO. Created the interface with Figma and built the frontend using ReactJS, incorporating state management for seamless user interactions. Utilized Material UI for efficient UI implementation and hosted the site on Firebase for easy accessibility.
Tags: Figma Frontend Material UI React
Event Hosting Website
This project is condcted in group during internship at EDXL. During my internship at EDXL, I revamped the company website by leading a team of 5 interns. We focused on redesigning the website to enhance user experience and visual appeal using Figma. I developed the redesigned site using React.js and Bootstrap, ensuring responsiveness and modern design standards. In addition, I implemented strategic planning and goal-setting processes, fostering collaboration and maintaining a positive work environment to achieve project milestones.
Tags: Bootstrap Figma Full Stack React
AI based Crop Disease Detection and Recommendation System
This project demonstrates the use of deep learning to predict plant diseases using the PlantVillage dataset. A Convolutional Neural Network (CNN) is designed for image classification, identifying healthy and diseased plants. The dataset is sourced from Kaggle, preprocessed for resizing and normalization, and split into training and validation sets. The model is trained with the Adam optimizer and evaluated for accuracy and loss metrics. It supports predicting disease classes for new images, with the trained model and class indices saved for future use.
Tags: Convolution Nerual Network Kaggle Matplolib Recommendation Sklearn Streamlit
Image Classification using ResNet
Image Classification using ResNet: Implemented ResNet152V2 architecture on the Animal10 dataset, enhancing accuracy with data augmentation and preventing overfitting with dropout connections. Developed a user-friendly interface using Streamlit for image uploads and deployed the model on Hugging Face Spaces for real-time classification tasks.
Tags: Convolutional Neural Network Hugging Face Image Classifier ResNet Streamlit
Movie Recommendation System
Developed a content-based movie recommendation system using machine learning algorithms and natural language processing techniques to recommend movies based on content attributes. Deployed the system on Hugging Face Spaces for easy access.
Tags: Content-Based Filtering Machine Learning Natural Language Processing Python