: Explains complex concepts including AdaBoost , XGBoost , and Convolutional Neural Networks (CNNs) for image-specific tasks.
: Focuses on building, training, and deploying models for practical use cases like facial recognition and object detection.
: Guides readers through the process of creating real-time models and deploying them for customized applications. Practical Machine Learning and Image Processing...
: Covers the initial setup for different operating systems and basic image processing terminology.
The book by Himanshu Singh (Apress, 2019) focuses on the practical application of image processing and machine learning algorithms using Python. Key Features of the Book : Explains complex concepts including AdaBoost , XGBoost
The book is designed to take readers from foundational concepts to advanced machine learning and deep learning methods specifically tailored for interpreting visual data. Practical Machine Learning and Image Processing
: Provides hands-on implementation using essential Python libraries such as OpenCV and Scikit-Image . : Covers the initial setup for different operating
: Masters techniques such as SIFT (Scale-Invariant Feature Transform) and RANSAC (Random Sample Consensus) to build efficient applications.