Utkarsh Kuchhal's repositories
BookManagementSystem-Golang
The Book Management System is a project that helps users manage their book collections effectively. The system is built using the MongoDB database, which provides a high-performance, scalable, and fault-tolerant data store. The application allows users to add, edit, delete, and search for books in their collection.
Chicken-Disease-Classification
This project is a comprehensive MLOps endeavor focused on classifying chicken diseases using advanced deep learning techniques, particularly LSTM neural networks. Leveraging Docker and DVC (Data Version Control), the pipeline is meticulously crafted to streamline the deployment and management of the deep learning model.
Complete-Placement-Preparation
This repository consists of all the material required for cracking the coding rounds and technical interviews during placements.
Django-Recipe-Finder
A Django web application that allows users to search, add, view, and delete recipes. Recipes are stored in a MongoDB database and images are saved in the static files directory. Redis is used for caching to improve search performance.
Expense-Tracker-App
Expense Tracker Web Application helps you keep track of your monthly expenses and income conveniently. The application is built using MERN stack, and it utilizes the MongoDB Atlas database to securely store your financial data.
Named-Entity-Recognition-NER-using-Transformers
Named Entity Recognition (NER) using Transformer Model
Real-Time-Chat-App
Real-Time Chat is powered by Socket.IO. It is a web application that allows multiple users to have a private and public chat. This app allows one to one chat online and its fast and easy to use.
Customer-Churn-Prediction
Customer Churn Prediction is a machine learning project aimed at predicting whether a specific user will leave a service or not. The project involves extensive exploratory data analysis (EDA), model training and deployment of a Streamlit web application for user interaction.
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
DeepSteganography
Ever sent a hidden message in invisible ink to your friends? Are you intrigued by the idea of cryptic message exchange? How about using images for this exchange? Steganography is what you need! It is one of the techniques of encryption and over the years, steganography has been used to encode a lower resolution image into a higher resolution image. But steganography using naive methods, like LSB manipulation, is susceptible to statistical analysis. Our model extends existing deep learning research for encoding multiple secret images onto a single cover by leveraging convolutional neural networks based deep learning architectures. DeepSteg allows senders to embed up to three secret images onto a single cover using an encoder network and then have multiple decoder networks to obtain the embedded secrets.
FAANG
Facebook, Amazon, Apple, Netflix and Google (FAANG) Job preparation.
HackOverflow
Problem Statement: You are working on an autonomous underwater vehicle that is navigating underwater avoiding obstacles and achieving targets. In the navigation there comes a gate of which you know the dimensions and color. The bot must pass through it without touching it in order to complete the mission. You have to write code for detecting the gate and to know its center in order for the bot to pass through it. You will get the raw images from the camera and you’ll have to perform image processing on it and get the results.
LLM-News-Research-Tool
User-friendly news research tool designed for effortless information retrieval. Users can input article URLs and ask questions to receive relevant insights from the stock market and financial domain.
Movie-Sentiment-Analysis-BERT
Trained a basic model to get a deep understanding of BERT