Vision Geek

YOLO is one of the most widely used object detection models in the industry, known for its speed and accuracy. YOLOv11, the latest release from Ultralytics (the team behind YOLOv5 and YOLOv8), brings cutting-edge advancements to the YOLO family.

In this hands-on online workshop, you'll explore YOLOv11 in depth and gain practical skills to build and deploy custom object detection models.

What You’ll Learn:

1. What’s new in YOLOv11: Key updates and features.
2. Architecture overview: Understand the structure of YOLOv11.
3. Model variants: Discover available versions and their applications.
4. Running inference: Use pre-trained YOLOv11 models for predictions.
5. Dataset preparation: Gather and annotate a custom dataset for object detection.
6. Model training: Train a custom YOLOv11 object detection model using the gathered dataset using fine-tuning / transfer learning.
7. Evaluation metrics: Analyze your model’s performance in detail.
8. Model deployment: Export and test your trained model on unseen images, videos, or live webcam feeds.
9. Performance optimization: Learn strategies to enhance model accuracy and efficiency.

This is a live, hands-on workshop where participants can follow along, apply what they learn immediately, and build practical skills. Participants can ask questions and clarify doubts right then and there.

Whether you're a beginner or a professional looking to upgrade your skills, this workshop will provide practical insights and coding experience to develop your own custom object detection applications and harness the full potential of YOLOv11 for your projects.

Prerequisites:

1. Basic experience with Python programming
2. Basic understanding of running object detection models on images/videos

All skill levels are welcome. Participants will receive an e-certificate upon completion of the workshop.

About the Instructor

Arun Ponnusamy holds a Bachelor’s degree in Electronics and Communication Engineering from PSG College of Technology, Coimbatore. With a decade of experience as a Computer Vision Engineer in various AI startups, he has specialized in areas such as image classification, object detection, object tracking, human activity detection, and face recognition. As the founder of Vision Geek, an AI education startup, and the creator of the open-source Python library “cvlib,” Arun is committed to making computer vision and machine learning accessible to all. He has led workshops at institutions like VIT and IIT and spoken at various community events, always aiming to simplify complex concepts.

LinkedIn: linkedin.com/in/arun-ponnusamy