I'm a student with a passion for coding, designing, and exploring new technologies. On this journey of learning and creating, I aim to build projects that make a difference. Join me as I grow and showcase my skills!
More About MeI'm a dedicated problem solver with a passion for tackling challenges head-on. As a student, I've honed my skills in critical thinking, creativity, and analytical reasoning to find effective solutions to complex problems. Whether it's coding, logical puzzles, or real-world challenges, I enjoy breaking problems down into manageable parts and exploring innovative approaches. My curiosity drives me to constantly learn, adapt, and improve, making me a versatile and resourceful individual. I believe that every problem is an opportunity to grow and innovate, and I strive to make a positive impact by applying my skills to meaningful projects.
I'm a passionate tech enthusiast with certifications in Cloud Computing, Machine Learning (ML), and Data Science. I thrive on exploring innovative technologies and solving complex problems. With a deep understanding of cloud infrastructure, data analytics, and machine learning algorithms, I'm driven to apply these skills to create impactful solutions and contribute to cutting-edge projects. I believe in continuous learning and growth, always staying updated with the latest advancements in the tech world. Let's connect and explore new opportunities in the ever-evolving tech landscape!
Graphic Era University
CGPA:8.89
Major: Computer Science Engineering
Hilton's School
Percentage: 89.8%
Board : ISC (Science)
Hilton's School
Percentage: 95.12%
Board: ICSE (Science)
This Project is a vizualizer for phases of Compiler, developed as an educational tool to illustrate phases of Compiler. It shows how a Compiler processes a source code through various phases upto the Parse Tree Generation.
Phases it Covers :-
*Lexical Analyzer: Helps to Generate tokens traced from source code and build a Symtab.
*Syntax Analysis: Uses Grammar rules to check for syntactic errors in the code.
*Parse Tree Generation: Generates .png files to represent the parse tree.
*Semantic Analysis: Checks for undeclared variables and all other semantic errors.
Technologies Used:-
*Languages: C/C++ , Python, Javascript
*Tools: Lex (Lexical Analysis), YACC (Parser Generator), Graphviz (Parse Tree Vizualization)
A simulation of Smart Resource Management focusing on:
*Efficient Resource Allocation.
*Deadlock Detection and Prevention
*Implementation of Bankers Algorithm and Resource Allocation Graph.
Features :-
*Simulates multiple processes and resource types.
*Implements Banker’s Algorithm for safe resource allocation and Generation of Resource Allocation Graph.
*Deadlock Recovery Module: Suggests a process to terminate in case of a deadlock Recalculates the safe sequence after removal.
*Web-based frontend for interactive simulations and Converts RAG to Wait-for Graph (WFG) for deadlock detection.
Technologies Used:-
*Languages: Python, Javascript
*Tools: Flask - Backend web framework, MatplotLib - For graph Vizualization
A comprehensive Streamlit application designed to assist in medical diagnostics through advanced machine learning models. The app provides a seamless and user-friendly
Interface for healthcare professionals and works across three major functionalities:
Diabetes Prediction: Users can input key health metrics, and the app predicts the likelihood of diabetes using a Logistic Regression model. The model was trained on a Kaggle dataset containing 1,000 datapoints, ensuring accurate and reliable predictions.
Brain Tumor Detection: By analyzing MRI scans, the app identifies the presence of brain tumors. The model was trained on a dataset of 4,000 MRI images, ensuring high sensitivity and specificity in tumor detection.
Skin Cancer Classification: The app classifies skin conditions into 7 types of skin cancer or identifies healthy skin using a state-of-the-art deep learning model. Trained on 30,000 high-quality images, the model provides accurate and actionable results to assist dermatologists. This app showcases the power of machine learning in healthcare, providing accurate predictions and enhancing diagnostic efficiency.
SIC and SIC/XE Assembler (Fully Functional) Year: 2024
This project involves the development of an assembler for the SIC (Simplified Instructional Computer) and SIC/XE architecture, which are used in computer architecture courses to teach assembly language and machine-level programming. The assembler translates assembly code into machine code that can be executed on the SIC or SIC/XE system.
Key features of the project include:
* Full Functionality: The assembler is capable of handling both SIC and SIC/XE instruction formats, supporting various operations such as loading,storing, and arithmetic operations.
* Error Checking: It includes robust error handling for syntax errors, operand errors, and invalid instructions, ensuring smooth debugging and learning.
* Symbol Table: The project maintains a symbol table for variable addresses and labels, allowing the assembler to manage memory addresses efficiently.
* Support for Extended Operations (SIC/XE): The SIC/XE version includes additional instruction formats (e.g., the extended format) to allow more complex operations, such as floating-point arithmetic and larger memory address space.
* Optimized Code Generation: The assembler generates efficient machine code, translating high-level assembly instructions into optimized machine instructions.
This project demonstrates a strong understanding of assembly language programming, computer architecture, and the translation of high-level code into machine-readable formats. It serves as an essential tool for learning low-level computer systems programming.
A simple calculator built using Java Swing for basic arithmetic operations like addition, subtraction, multiplication, and division. The application features a clean, user-friendly interface with buttons for digits, operations, and clear/equals functionality. It handles errors gracefully and provides real-time results.
Key Features:
* Performs basic arithmetic operations
* Clear and equals functionality
* Error handling (e.g., divide by zero)
* Responsive layout using Java Swing
Technologies Used:
* Java (Core Programming Language)
* Swing (GUI Toolkit)
C / C++, Python, Java, SQL, Html, CSS ,Javascript
Machine Learning, Deep Learning, Data Structure and Algorithms,
AI, Data Science, Front End Development
Jupyter Notebook, Visual Studio Code, Google Collab, GitHub,