February 2018
Beginner to intermediate
234 pages
6h 5m
English
Overview
Dive into the world of computer vision with 'Practical Computer Vision'. From foundational techniques to advanced deep learning models, this book equips you with the tools and knowledge to analyze and interpret images. Perfect for enthusiasts and professionals alike, you'll explore Python libraries like TensorFlow, Keras, and OpenCV to create impactful vision solutions.
What this Book will help me do
- Understand basic image manipulation techniques using Python and OpenCV.
- Learn to set up and utilize ML libraries including TensorFlow and Keras for image classification.
- Master advanced topics such as object detection and tracking using convolutional neural networks.
- Gain proficiency in semantic segmentation and Visual SLAM (Simultaneous Localization and Mapping).
- Apply these techniques to real-world datasets, preparing you for practical applications.
Author(s)
Abhinav Dadhich, a seasoned expert in machine learning and computer vision, brings years of practical experience to this book. With a passion for teaching and simplifying complex topics, Abhinav ensures that readers not only learn, but also apply these skills effectively. His writing connects the theory to implementation with hands-on examples.
Who is it for?
If you're a machine learning practitioner aiming to delve into computer vision or a deep learning enthusiast eager to deploy vision techniques, this book serves as an ideal stepping stone. Programming background is helpful, and Python knowledge will significantly enhance your learning. In essence, it's best suited for learners transitioning theoretical knowledge into practical vision solutions.
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