Computer Vision (AI and ML Reference handbooks)

Master Computer Vision from First Principles to Production Systems

Whether you're a student, AI engineer, software developer, researcher, or interview candidate, this comprehensive guide takes you from the fundamentals of computer vision to building production-ready AI applications. The book is designed as both a practical reference and a graduate-level learning resource, covering the mathematics, algorithms, deep learning architectures, deployment strategies, and real-world implementation of modern computer vision systems.

Inside this book, you'll learn:

• Image fundamentals, pixels, color spaces, and digital image representation
• Classical computer vision techniques including filtering, edge detection, feature extraction, and segmentation
• Convolutional Neural Networks (CNNs) from fundamentals to implementation
• Modern object detection algorithms including YOLO
• Semantic and instance segmentation using U-Net and Mask R-CNN
• Transfer Learning and pretrained vision models
• Vision Transformers (ViTs)
• GANs, Diffusion Models, and Generative Computer Vision
• 3D Computer Vision, Camera Geometry, and Depth Estimation
• Video Analytics, Object Tracking, and Action Recognition
• Foundation Vision Models including CLIP, SAM, Grounding DINO, Florence-2, and DINOv2
• Vision-Language Models and multimodal AI
• Production deployment, optimization, monitoring, and MLOps for Computer Vision
• Three complete end-to-end capstone projects with production workflows
• Interview questions and answers in every chapter
• Practical Python implementations using OpenCV, PyTorch, Ultralytics YOLO, and Hugging Face libraries

Unlike books that focus only on theory or only on code, this guide combines intuitive explanations, mathematical foundations, architecture diagrams, production engineering practices, and hands-on implementations into one complete reference.

Whether you're preparing for technical interviews, building production AI systems, pursuing graduate studies, or expanding your professional skills, this book provides a practical roadmap from pixels to intelligent vision systems.

Perfect for:

• AI & Machine Learning Engineers
• Computer Vision Engineers
• Data Scientists
• Software Developers
• Graduate & Undergraduate Students
• Researchers
• Technical Interview Preparation
• Professionals building production AI applications