Advanced Color Image Processing and Analysis

Quickly obtain solutions to common Java image processing problems, learn best practices, and understand everything OpenCV has to offer for image processing. You will work with a JVM image wrapper to m

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapt

Gain insights into image-processing methodologies and algorithms, using machine learning and neural networks in Python. This book begins with the environment setup, understanding basic image-processing terminology, and exploring Python concepts that will be useful for implementing the algorithms discussed in the book. You will then cover all the core image processing algorithms in detail before moving onto the biggest computer vision library: OpenCV. You’ll see the OpenCV algorithms and how to use them for image processing. The next section looks at advanced machine learning and deep learning methods for image processing and classification. You’ll work with concepts such as pulse coupled neural networks, AdaBoost, XG boost, and convolutional neural networks for image-specific applications. Later you’ll explore how models are made in real time and then deployed using various DevOps tools. All the concepts in Practical Machine Learning and Image Processing are explained using r

Utilize modern methods for digital image processing and take advantage of the many time-saving templates provided for all of the projects in this book.Modern Algorithms for Image Processing appro

Quickly learn how to automate unit testing of Python 3 code with Python 3 automation libraries, such as doctest, unittest, nose, nose2, and pytest.This book explores the important concepts in software

Each book aims to teach an important technology or programming language and is designed to take a person from being a novice to a professional by including the most essential information and explainin

From the elegance of the Black-Scholes equation to the complexity of multi-factor interest rate models and hybrid derivatives, this book is your comprehensive guide to quantitative finance, complete with 15+ advanced C++ projects using QuantLib and Boost.You'll move seamlessly from mathematical foundations to real-world implementation, building a professional-grade toolkit for pricing, risk analysis, and calibration. Inside, you will learn core option pricing methods, master single-and multi-factor interest rate models, and construct and calibrate trees and lattices for advanced derivatives. You will also explore cutting edge products: exotic multi-asset options, hybrid derivatives, credit instruments, and cross-currency swaps.Packed with practical source code, step-by-step calibrations, and performance-tuned Boost integration, this book bridges the gap between academic finance and production-grade quant development. Whether you're a quant developer, financial engineer, or an advanced

Discover the potential applications, challenges, and opportunities of deep learning from a business perspective with technical examples. These applications include image recognition, segmentation and

Master functions and discover how to write functional programs in R. In this concise book, you'll make your functions pure by avoiding side-effects; you’ll write functions that manipulate other functi

Carry out data analysis with PySpark SQL, graphframes, and graph data processing using a problem-solution approach. This book provides solutions to problems related to dataframes, data manipulation su

Closely examine website scraping and data processing: the technique of extracting data from websites in a format suitable for further analysis. You'll review which tools to use, and compare their

Learn how to write object-oriented programs in R and how to construct classes and class hierarchies in the three object-oriented systems available in R. This book gives an introduction to object-orien

Learn how to manipulate functions and expressions to modify how the R language interprets itself. This book is an introduction to metaprogramming in the R language, so you will write programs to manip

Learn the intricate workings of DAX and the mechanics that are necessary to solve advanced Power BI challenges. This book is all about DAX (Data Analysis Expressions), the formula language used in Power BI―Microsoft’s leading self-service business intelligence application―and covers other products such as PowerPivot and SQL Server Analysis Services Tabular. You will learn how to leverage the advanced applications of DAX to solve complex tasks.Often a task seems complex due to a lack of understanding, or a misunderstanding of core principles, and how certain components interact with each other. The authors of this book use solutions and examples to teach you how to solve complex problems. They explain the intricate workings of important concepts such as Filter Context and Context Transition. You will learn how Power BI, through combining DAX building blocks (such as measures, table filtering, and data lineage), can yield extraordinary analytical power. Throughout Pro Dax with Power BI t