Expand your OpenCV knowledge and master key concepts of machine learning using this practical, hands-on guide.
About This Book
- Load, store, edit, and visualize data using OpenCV and Python
- Grasp the fundamental concepts of classification, regression, and clustering
- Understand, perform, and experiment with machine learning techniques using this easy-to-follow guide
- Evaluate, compare, and choose the right algorithm for any task
Who This Book Is For
This book targets Python programmers who are already familiar with OpenCV; this book will give you the tools and understanding required to build your own machine learning systems, tailored to practical real-world tasks.
What You Will Learn
- Explore and make effective use of OpenCV's machine learning module
- Learn deep learning for computer vision with Python
- Master linear regression and regularization techniques
- Classify objects such as flower species, handwritten digits, and pedestrians
- Explore the effective use of support vector machines, boosted decision trees, and random forests
- Get acquainted with neural networks and Deep Learning to address real-world problems
- Discover hidden structures in your data using k-means clustering
- Get to grips with data pre-processing and feature engineering
In Detail
Machine learning is no longer just a buzzword, it is all around us: from protecting your email, to automatically tagging friends in pictures, to predicting what movies you like. Computer vision is one of today's most exciting application fields of machine