Dedicated to exploring the realms of technology, and eager to contribute innovative solutions to the ever-evolving IT landscape.
PROJECT SHOWCASE
I led a four-member team to develop a Placement Cell web app as part of my degree curriculum, overseeing documentation and preparing the SRS report. The app connects students and recruiters by providing an intuitive platform where students can register, explore job opportunities, and apply directly, while recruiters can post job openings. Additionally, it features a discussion forum to foster communication and collaboration between both parties, creating a seamless and efficient recruitment process. This platform aims to bridge the gap between talent and job opportunities, ensuring a smooth placement experience for everyone involved.
This Blogging WebApp project allows users to create, read, update, delete, like, and comment on blogs. Built with Flask and SQLAlchemy, it also features personalized recommendations based on user activity and blog summaries generated using the Gemini API. Key functionalities include secure user authentication, the ability to add images to blogs, and password hashing using PBKDF2 for security. The app also provides users with blog summaries and ensures an interactive experience with CRUD operations, personalized content, and an intuitive UI.
TechFolio is a personal portfolio website designed to showcase Kushal Gupta's technical skills, projects, and achievements. The site highlights his work in the tech industry, featuring links to his GitHub, LinkedIn, Instagram, and other social media profiles. Key features include a project showcase, a list of skills and technologies, and easy contact access. The site is built using HTML5 for structure, CSS3 for styling, JavaScript for interactivity, and a responsive design to ensure a great user experience across all devices. The portfolio also includes an about section, detailed project descriptions, and contact information for direct communication.
ProjectFolio is a personal portfolio website for Kushal Gupta, a student pursuing a Bachelor's Degree in Information Technology at Ganpat University. It serves as a centralized hub for showcasing his open-source projects like the Book Recommender System, Virtual Voice Assistant, Weather App, and more. The website also provides links to his other platforms, including TechFolio and the Telegram Chat Bot, as well as his social media profiles on GitHub, LinkedIn, Instagram, and WhatsApp. The website is built with HTML5 for structure, CSS3 for styling, and features a responsive design to ensure it looks great on any device.
The To-Do List with Firebase is a simple web app that uses Firebase Realtime Database to manage tasks. Users can add tasks to the list and delete them by clicking on any task. The app ensures real-time updates, meaning any changes to the task list are automatically reflected across all clients. Key features include task addition, real-time updates, and task deletion. It is built with Firebase for real-time database integration, along with HTML, CSS, and JavaScript for the front-end. The app allows seamless synchronization, making it easy for users to manage their to-do lists efficiently.
Introducing an intelligent book recommendation system driven by sophisticated content analysis. Using a comprehensive dataset featuring 1750 books from Kaggle, this project employs advanced content-based filtering techniques. By creating vectors based on various content features such as genre, author, and plot keywords, the system excels at understanding the unique difference and similarity of each book. Users can seamlessly discover new books by inputting their favorite book, and the system responds with a tailored list of content-wise related recommendations. Additionally, the system ensures to suggest all books of the same genre, providing users with a comprehensive selection within their preferred literary landscape. The streamlined frontend, crafted with Streamlit, ensures a user-friendly experience, making book exploration both personalized and enjoyable. This project gives book recommendations by prioritizing content relevance and user satisfaction, while also broadening the reader's horizons within their preferred genres.
Introducing WhatsApp Chat Analyzer, a powerful tool crafted with Python and Streamlit, designed to provide users with comprehensive insights into their WhatsApp chat data. From total message counts to word frequencies, media shared, and even links exchanged, this tool offers a multifaceted analysis of your conversations. Delve deeper into your chat history with features like monthly activity timelines, identifying your most active periods, and visualizing geographic activity patterns through interactive maps. Uncover trends and patterns with ease through word clouds highlighting frequently used terms. Whether for personal reflection or group analysis, WhatsApp Chat Analyzer offers a robust platform for exploring the dynamics of your conversations in depth.
This project is an advanced virtual desktop assistant developed in Python. It allows users to interact with their computer using voice commands, and the assistant responds with a synthesized voice. The assistant can perform various tasks, such as playing specific music, opening predefined applications, navigating to particular websites, displaying the current time. It can also engage in voice-based conversations with ChatGPT 3.5. This comprehensive assistant provides a user-friendly and interactive experience, leveraging voice recognition and artificial voice generation technologies.
SignLangSync is a real-time sign language recognition web-based project developed as part of a hackathon, where I led a 6-member team. The app uses a webcam to capture images and employs transfer learning with MobileNet and a K-Nearest Neighbors (KNN) classifier to recognize custom sign language gestures. Users can add new sign classes, capture images for training, and make predictions using webcam input. The app also offers speech feedback through the Web Speech API, providing audible predictions. Key features include real-time webcam input, custom sign language class training, model persistence (saving and loading models), and the ability to classify and identify signs. The project leverages TensorFlow.js and other web technologies to run entirely in the browser, allowing easy interaction and model updates.
The Image Processing Windows Application is a desktop software built using Visual Basic, Visual Studio 2019, and Emgu CV 4.5, designed to perform various image processing tasks. It includes basic functions such as grayscale conversion, binarization, and edge detection, along with advanced morphological operations like dilation, erosion, and gradient-based transformations. The application also offers object detection features like face and eye detection, QR code generation and detection, and optical character recognition (OCR). Additionally, it incorporates COVID-19-related image processing. Future improvements aim to integrate deep learning-based object detection and optimize real-time video processing.
Introducing a responsive weather forecasting project seamlessly integrated with the OpenWeatherMap API. It provides users with real-time weather updates and future predictions for any location worldwide. With the option to input a specific location or utilize the "use current location" feature, users can effortlessly access accurate weather data tailored to their needs, whether on desktop or mobile devices. The project not only displays current weather conditions but also offers a detailed forecast for the next five days, empowering users to plan ahead with confidence. Through intuitive design and reliable data retrieval, this responsive project ensures a seamless user experience across all devices, making it easier than ever to stay informed about weather patterns and make informed decisions accordingly.
The Online Music Visualizer is an interactive web app built with JavaScript that creates real-time animations based on audio frequencies. Users can upload and play audio files, with the app generating dynamic bar visualizations and floating particle effects that respond to the music. The visualizer features a responsive canvas animation and user-controlled playback for an engaging experience. Built using HTML5 for structure, CSS3 for styling and animations, and JavaScript for interactivity, the app leverages the Web Audio API to analyze audio data and the Canvas API to render visual effects. Upcoming features include a color-changing visualizer, beat detection, and 3D depth effects.
During my internship at CodSoft, I led the development of several data science projects. These projects involved tasks like filtering data and building models to predict outcomes based on given inputs. I used tools like LogisticRegression, LinearRegression, RandomForestRegression, and Ridge from sklearn to train these models. Additionally, I used seaborn for easy-to-understand data visualization. The data for these projects was obtained from platforms like Kaggle, ensuring its quality and relevance. Some notable projects I worked on include predicting Titanic survival, movie ratings, iris flower types, and sales. Each project required a good grasp of data science concepts and careful model training.
As part of the interview process at BrainyBeam, I completed several tasks that involved Django development and Python programming. These tasks included building a Quiz App with dynamic question options, developing a Time Complexity Analyzer to measure execution time, and creating a POST API using Django REST Framework to handle post creation and count. Additionally, I integrated an external API to fetch city data and export it into a CSV file. I also demonstrated key object-oriented programming concepts, such as Polymorphism and Encapsulation, in a Python program. These tasks helped me strengthen my skills in web development, APIs, and data handling.