Computer Engineer | AI Enthusiast

khuzaima zarar  • Peerlist

I trained a Linear Regression model to predict student scores based on study hours using Python & Scikit-learn.

predict student scores based on study hours

🚀 Project Showcase: 3x3 Bit Binary Multiplier Built in Logisim! 💻 I recently designed and implemented a 3x3 bit binary multiplier using Logisim, a digital logic simulator. This project multiplies two 3-bit binary numbers (a2a1a0 and b2b1b0) to produce a 6-bit product, demonstrating fundamental concepts of digital arithmetic circuits. Practical uses of this multiplier include: Core component in Arithmetic Logic Units (ALUs) Essential in Digital Signal Processing (DSP) tasks Building block for more complex multipliers in hardware design Useful for embedded systems requiring efficient, low-bit-width multiplication Building this project helped me deepen my understanding of binary multiplication, partial product generation, and digital circuit design.

3x3 Bit Binary Multiplier Built in Logisim

Restaurant Management System (SQL & PHP) A dynamic web-based application designed to streamline restaurant operations. Built with PHP and backed by an SQL database, this system manages menu items, customer orders, reservations, billing, and staff roles. It offers a user-friendly interface for both administrators and customers, enhancing efficiency and improving overall dining experience.

Restaurant management system (sql) database a

In this project, I've developed a playlist management system using fundamental data structures like linked lists. The playlist allows users to: Add songs to the playlist Remove songs from the playlist Display the current playlist in the order of songs Navigate through songs (next and previous) Search for a song by its name

mp3 Playlist

I developed a CPU scheduling simulator in C language that models how an operating system handles processes. The project supports multiple scheduling algorithms such as FCFS, SJF, SRTF, Priority Scheduling, and Round Robin. It generates Gantt charts, computes completion, waiting, and turnaround times, and provides a clear comparison between algorithms. This project helped me strengthen my understanding of OS concepts and process management.

OS Scheduling Simulator

regisration form for web development

Implemented a machine learning model for breast cancer detection. Included data preprocessing, train-test split, model training, evaluation, and accuracy reporting. Added Jupyter Notebook with detailed steps and visualizations for model performance.

Breast cancer detection

The dataset (advertising.csv) contains 200 rows and 4 columns: TV: advertising budget spent on TV ads (in thousands of dollars) Radio: advertising budget spent on Radio ads Newspaper: advertising budget spent on Newspaper ads Sales: sales of the product (in thousands of units) So, the dataset shows how money spent on ads affects product sales. Goal of the Project The main objective is to predict sales based on advertising budgets (TV, Radio, Newspaper). This is a multiple linear regression problem because sales depend on multiple factors (features). Steps Done Data Import & Preparation Loaded the dataset. Separated input features (x = TV, Radio, Newspaper) and target (y = Sales). Split data into training (60%) and testing (40%) sets. Model Training Used LinearRegression from scikit-learn. Fit the model on training data. Model Parameters Coefficients (model.coef_): TV → 0.0546 Radio → 0.1114 Newspaper → 0.0061 This means: if we increase TV ad spend by 1 unit, sales increase by ~0.0546 units (keeping others constant). Intercept (model.intercept_): 4.43 (baseline sales when ad spend = 0). Model Evaluation On Training data: R² = 0.917 → Very good fit (91.7% variance explained) MAE ≈ 1.19 → Average error is about 1.19 sales units MSE ≈ 2.31 On Testing data: R² = 0.877 → Good generalization MAE ≈ 1.30 MSE ≈ 3.38 Conclusion This project is about building and evaluating a linear regression model to predict product sales from advertising budgets in TV, Radio, and Newspaper. 👉 Basically, it answers the business question: “How should we allocate advertising budget to maximize sales?”

This project is a machine learning regression

"MATLAB-Based Curve Fitting for Thermodynamic Data Analysis" "Modeling Pressure-Temperature Relationship Using Polynomial Regression" "Predictive Analysis of Pressure Using Quadratic Polynomial Fit"

Pressure Prediction Using Quadratic Curve Fit

Hospital Management System | C++ | Object-Oriented Programming (OOP) I recently completed a comprehensive Hospital Management System using C++, showcasing key principles of Object-Oriented Programming (OOP) such as encapsulation, inheritance, polymorphism, and abstraction. The system efficiently handles the core functionalities of hospital management, including: Patient registration and management Doctor and staff information management Appointment scheduling Billing and invoicing Medical record handling Key features of the project: Modular design with classes for patients, doctors, hospital staff, and departments Extensibility allowing easy addition of new functionalities Inheritance structure for handling different user roles (admin, doctor, patient) Data encapsulation ensuring secure handling of sensitive information Polymorphism to manage diverse user interactions File handling to store patient records and retrieve them efficiently This project helped solidify my understanding of OOP principles and enhanced my skills in C++ programming. It also demonstrated how software solutions can streamline complex operations in the healthcare industry. Excited to keep building and learning more!

Hospital management

🚀 Project Update: 32-bit ALU (Arithmetic Logic Unit) Built in Logisim 💻⚙️ I’m excited to share that I’ve successfully designed and implemented a 32-bit ALU (Arithmetic Logic Unit) using Logisim, as part of my computer engineering journey! 🔧 What is an ALU? An ALU is the core component of a CPU that performs arithmetic and logical operations. My 32-bit ALU can handle operations like: Addition Subtraction AND, OR, XOR Shift operations Zero and negative result detection 💡 Why it matters: This project gave me hands-on experience with digital logic design, bitwise operations, and how real-world processors manage complex computations internally. It’s a foundational step toward understanding how CPUs execute instructions at the hardware level. Special thanks to my professors and peers who supported this journey! Looking forward to more hardware-based innovations 🚀 #Engineering #Logisim #ComputerArchitecture #ALU #HardwareDesign #DigitalLogic #StudentProject #32bitALU #ComputerEngineering

32 bit ALU

Empowering the Visually Impaired with Innovative Technology I am excited to share my latest project: Arduino-Powered Smart Gloves for the Visually Impaired. These gloves are designed to enhance independence and mobility for blind individuals by using sensors and haptic feedback to detect obstacles and provide real-time guidance. Key features include: 🔹 Ultrasonic sensors for precise obstacle detection. 🔹 Vibrational feedback to alert users to nearby objects. 🔹 Compact, lightweight, and comfortable design for everyday use. 🔹 Open-source code for further customization and development. This project reflects my commitment to harnessing technology for inclusive solutions. I’m open to feedback, collaboration, and discussions on how we can refine and scale this innovation to make a meaningful impact. #AssistiveTech #Innovation #Accessibility #ArduinoProjects

Arduino gloves for blind people

I developed a Random Game Generator using C++, which allows users to randomly select a game from a predefined list of options. The program utilizes C++ concepts like arrays, random number generation, and control structures to efficiently display a game recommendation. It provides an interactive and fun way to choose a game, especially when indecisive about what to play next!