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šŸ’« About Me:

šŸ”­ Iā€™m currently working on AI Generated Text Detection
šŸ¤ Iā€™m looking for help with Tensorflow, django
šŸŒ± Iā€™m currently learning Tensorflow, django

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šŸ’» Tech Stack:

C C++ CSS3 JavaScript HTML5 R Python GithubPages Netlify Vercel Anaconda Bun Django Flask Jinja NPM TailwindCSS React OpenCV Green Sock WordPress MongoDB MySQL Adobe Lightroom Blender Canva Keras Matplotlib mlflow NumPy Pandas Plotly PyTorch scikit-learn Scipy TensorFlow Notion TOR

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Shaik Mohammad Asrar Ahammad's Projects

object-detection-classification-tracking icon object-detection-classification-tracking

This project uses the Ultralytics YOLO object detection framework and the supervision library to detect and track objects in a video stream. It annotates the detected objects with boxes and labels and counts the number of objects that cross a specified line.

portfolio icon portfolio

The Portfolio Website repository showcases a professional portfolio website that highlights your skills, projects, and achievements. It serves as a digital representation of your work and expertise.

student-performance-prediction icon student-performance-prediction

The Student Performance Analysis System is a machine learning-based solution that analyzes student performance using various features. It leverages a CI/CD pipeline and is yet to deployed on Streamlit for automated development, testing, and deployment.

sundown-clone icon sundown-clone

Sundown Studio Clone showcases advanced CSS animations, smooth scrolling, modern UI design with hover effects, cycling text animation, and captivating gradient circle animation, built with HTML, CSS, JavaScript, and libraries like Locomotive Scroll.

text-classification icon text-classification

This repository implements deep learning models to distinguish between human-authored text and text generated by artificial intelligence.

traffic-sign-detection icon traffic-sign-detection

This project employs the YOLOv5 algorithm to train a specialized model capable of accurately detecting traffic signs. The objective is to enhance road safety and optimize traffic management through efficient and reliable traffic sign recognition.

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