Lakshin Pathak's Projects
This repository contains a simple yet robust banking application implemented in Python using the Tkinter library for the graphical user interface (GUI). The application allows users to perform basic banking operations such as account creation, balance inquiry, funds transfer.
This repository contains the source code for a web application that performs crop disease detection using the EfficientNet architecture. The application is built with Flask, a lightweight Python web framework, and leverages a pre-trained EfficientNet model for accurate and efficient disease classification.
This CSV File Visualizer is a web application built with HTML, CSS, Node.js, Express, and MongoDB. The project focuses on providing users with a powerful tool to analyze and visualize data from CSV files, offering features such as bar graphs, pie charts, histograms, group-by queries, and statistical calculations.
This is an Doctor Patient Appointment web application built with Node.js, Express, MongoDB, HTML, and CSS. These application allows users to efficiently organize, manage and book appointments.
Welcome to our E-Commerce website ā your one-stop destination for an immersive online shopping experience! This website is meticulously crafted using HTML, CSS, and JavaScript to provide you with a seamless and visually appealing platform for all your shopping needs.
This is an Event Management web application built with Node.js, Express, MongoDB, HTML, and CSS. The application allows users to efficiently organize, manage, and participate in various events.
This project uses TensorFlow and Keras to develop a deep learning model for detecting glasses on human faces in images. It employs convolutional neural networks (CNNs) to classify images into "with glasses" and "without glasses" categories, offering a versatile tool for applications like facial recognition and virtual try-on experiences.
This project implements a Graph Convolutional Network (GCN) using PyTorch Geometric for graph classification. The model is trained on the MUTAG dataset, which consists of chemical compounds labeled according to their mutagenicity.
The Loan Defaulter Application is a machine learning project aimed at predicting whether a bank loan applicant will default on their loan. The application uses a pre-trained model to make predictions based on various input features such as applicant income, loan amount, loan duration, credit history, and more.
The Movie Recommendation System is a web application designed to help users find movies tailored to their preferences. This project leverages the Gemini API, LangChain for language processing, and Streamlit for creating an interactive user interface.
An interactive social media platform crafted with HTML, CSS, Node.js, Express, and MongoDB. Users can chat, create posts, like, comment, and explore content shared by others, fostering seamless communication and engagement within a dynamic online community.
This project utilizes LSTM networks to produce text in the style of William Shakespeare. It delves into the blend of literature and AI by replicating the intricate linguistic features and poetic richness of Shakespeare's prose and poetry.