Software Engineer

The program is a simulation of a small Train control system for tfl. The system allows the user to have full control of the train records when logged in as an admin. Using CRUD operations.

The application simulates a Notepad/Text Editor, enabling users to generate documents. Within this system, users can initiate new files in the Notepad/Text Editor, open existing files, and save both new and existing files.

The Prediction of Stock Prices project is a sophisticated analytical tool developed in Python, designed to forecast stock market prices using historical data. This predictive model leverages a range of Python libraries, each serving a specialized function in the data processing and machine learning pipeline

The Dimensionality Reduction project delves into the realm of dimensionality reduction, a critical aspect of data analysis, particularly in understanding complex datasets like gene expression data. By employing three distinct techniques—PCA, LDA, and MDS— it aims to reduce the high-dimensional gene data into a lower-dimensional space. This process not only simplifies the visualization and interpretation of the data but also aids in uncovering hidden patterns and relationships.

The AI-Driven Music Composition project involves using deep learning techniques to generate music compositions in MIDI format. The code parses a collection of MIDI files, extracts musical notes and chords, and then trains a Long Short-Term Memory (LSTM) neural network to learn the patterns and structures within the music. Once trained, the model can generate new music compositions based on the learned patterns. The project aims to explore the creative potential of AI in music composition and provides a starting point for further experimentation and development in the field of generative music.

The AI Automation project is designed to predict customer churn in a simulated banking environment. It utilizes various R libraries and machine learning techniques to analyze customer data and identify patterns that indicate the likelihood of customers discontinuing their business with the bank. This project showcases how machine learning and AI can be utilized for predictive analytics in the banking sector, particularly in understanding and predicting customer behavior, such as churn. The methods and techniques used here can be adapted to various business analytics scenarios.

The application emulates a 32-bit system designed for floating-point numbers. It illustrates the processes of adding and subtracting two distinct 32-bit floating-point numbers. Additionally, the system handles the display of results on an 8-bit binary counter.

The application simulates a concise Neural Network Algorithm designed for answering questions. Within this system, users can input up to five numbers, and the calculations are performed using the neural network algorithm. The functionalities include working with a neural network, adding numbers, and obtaining results based on the algorithm.

The Flappy Bird Game project aims to recreate the popular mobile game "Flappy Bird" using web-based technologies. The game features a bird that the player controls, navigating through a series of obstacles. The primary objective is to achieve the highest possible score by avoiding collisions.

The Galaga project is a classic arcade game from 1981. The aim is to recreate the experience of the original fixed shooter game using modern web technologies. This version allows players to enjoy the nostalgic gameplay of Galaga directly in their web browsers. The Galaga Web Edition project serves as a testament to the timeless appeal of classic arcade games and demonstrates the versatility of HTML, CSS, and JavaScript in recreating such experiences. It offers both a nostalgic trip for those familiar with the original game and an engaging introduction to classic gaming for new players.

This project involves the development of a sophisticated Chat Application using React. The app's standout feature is its intelligent message grouping and presentation, designed to enhance readability and user interaction. This chat app project stands out with its focus on user-friendly message display and intelligent grouping. It's not just about sending and receiving messages, but also about presenting them in a contextually relevant and visually pleasing manner. The use of React underlines a commitment to modern, efficient, and robust web application development practices.

This Image Clustering project employs machine learning to categorize pixels or groups of pixels in an image into distinct clusters based on their similarities. An algorithm analyzes the input image, processes it using a model like K-means, and identifies patterns or features common to certain pixel groups. The result is a segmented image where each cluster represents a grouping of pixels with similar characteristics, such as color or intensity, visually simplifying the image into distinct regions.

The endeavor involves a Robot Simulation designed for personal utility. This simulation empowers users to command and control the robot, incorporating features such as Bluetooth pairing, interactions based on distance, environment scanning, and detection of obstacles in its path.

The software emulates a Voice Assistant Application (Gideon) tailored for efficient phone control. Users can navigate their phone and utilize Google Assistant for online searches through voice commands within the system, featuring Gideon Voice Assistant and integration with Google Assistant.

The platform revolves around Recipe Comments, providing a space for users to explore cooking recipes and share their additional comments. It features a comment form for user input and ensures the storage of provided data.