class DanishAfridi:
def __init__(self):
self.name = "Danish Khan Afridi"
self.role = "ML Engineer & Computer Vision Specialist"
self.education = "MSc Artificial Intelligence & Data Science @ University of Hull"
self.location = "Birmingham, UK 🇬🇧"
self.interests = ["Computer Vision", "Deep Learning", "Face Recognition", "Object Detection"]
def current_focus(self):
return [
"🔬 Dissertation: Fish Species Classification using Deep Learning",
"🖼️ Smart Gallery: AI-Powered Photo Management System",
"🚗 AutoVision: Vehicle Detection Platform (25K+ Users)"
]
def fun_fact(self):
return "I turn pixels into intelligence! 🧠✨"|
AI-Powered Photo Management System An intelligent photo gallery with face recognition, object detection, and semantic search capabilities. Tech Stack:
Features:
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Vehicle Detection & Classification Platform Production-ready computer vision platform for automated vehicle analysis with 25,000+ active users. Tech Stack:
Achievements:
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Deep Learning for Fishing Activity Monitoring MSc Dissertation project: Object detection and species classification using the FishNet dataset. Tech Stack:
Results:
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Machine Learning Experiment Tracking System A comprehensive platform for tracking ML experiments, model versions, and performance metrics. Tech Stack:
Features:
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AI-Powered Academic Research Assistant Intelligent tool for reading, analyzing, and understanding research papers with AI assistance. Tech Stack:
Features:
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Automated Computer Vision Model Training Platform for automated training and deployment of computer vision models with FastAPI backend. Tech Stack:
Features:
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I'm always open to interesting projects and collaborations in Computer Vision, Deep Learning, and Full-Stack AI Applications.
📧 Reach out: LinkedIn
⭐️ From Danish Khan Afridi with ❤️
