<About_Me>

Mohammed Uvez Khan

I am currently pursuing a Bachelor of Technology (BTech) in Computer Science and Engineering with a specialization in Artificial Intelligence and Machine Learning (AIML) at Dayananda Sagar University. I have built a strong foundation in programming, algorithms, and data analysis, focusing on AI and Machine Learning.

I am passionate about learning new technologies and applying them to real-world challenges. With experience in Python, machine learning, and project development, I am always looking for opportunities to contribute and grow.

</About_Me>

<Experience>

Infosys SpringBoard | Python Programming Intern

November 2024 - Present

Developing a scalable Learning Management System using Python to streamline education and training processes. Implementing features like role-based access, course management, and progress tracking for enhanced user experience.

Microsoft | Microsoft Learn Student Ambassador

July 2024 - Present

Organizing workshops and events to share knowledge and support learning among peers, focusing on technology and skill development. Collaborating with a diverse group of students worldwide to solve problems and create impactful projects.

GeeksforGeeks | Campus Mantri

July 2024 - Present

Collaborating with GeeksforGeeks to increase platform awareness and drive student participation in online resources, courses, and certification programs. Helping peers enhance their problem-solving and programming abilities.

</Experience>

<Skills>

</Skills>

<Projects>

Facial Recognition Model

Facial Recognition Model

Facial Recognition Model

A facial recognition model using Python and OpenCV for detecting and recognizing faces on camera. Utilized image processing techniques to detect faces and match them to a predefined dataset.

View Project
Image Enhancer

Image Enhancer

Image Enhancer

ESRGAN based Image Enhancer to increase the resolution and quality of blurry images.

View Project
Credit Card Fraud Detection

Credit Card Fraud Detection

Credit Card Fraud Detection

Machine learning model to detect credit card fraud with an accuracy of 95%. Used data preprocessing and feature selection techniques to improve model performance and identify fraudulent transactions.

View Project

</Projects>

<Resume>

Resume Preview

Download my resume to learn more about my qualifications and experience:

Download Resume (PDF)

</Resume>

<Connect_With_Me>

</Connect_With_Me>