The simplest way to create world-class apps Have a unique app idea but worried you don't quite have the coding skills to build it? Good news: You can stop fretting about someone beating you to market with the same idea and start work right now using SwiftUI. SwiftUI is a gateway app development framework that has become one of the best ways for fledgling developers to get iOS apps off the ground without having to become a coding expert overnight. SwiftUI For Dummies makes that process even faster, providing a friendly introduction to the SwiftUI and Swift programming language and helping you feel right at home creating and building with playgrounds. The book also covers the frameworks and APIs that make it so easy to create smooth, intuitive interfaces--just dive right in and have fun! Combine projects into workspaces Employ Xcode editing tools Use constants and variables Test your code on iOS Simulator Time is of the essence, and with SwiftUI For Dummies, it's also on your side. Get going with this friendly guide today, and you'll be celebrating the successful launch of your app way before you thought possible!

Python makes machine learning easy for beginners and experienced developers With computing power increasing exponentially and costs decreasing at the same time, there is no better time to learn machine learning using Python. Machine learning tasks that once required enormous processing power are now possible on desktop machines. However, machine learning is not for the faint of heart--it requires a good foundation in statistics, as well as programming knowledge. Python Machine Learning will help coders of all levels master one of the most in-demand programming skillsets in use today. Readers will get started by following fundamental topics such as an introduction to Machine Learning and Data Science. For each learning algorithm, readers will use a real-life scenario to show how Python is used to solve the problem at hand. - Python data science--manipulating data and data visualization - Data cleansing - Understanding Machine learning algorithms - Supervised learning algorithms - Unsupervised learning algorithms - Deploying machine learning models Python Machine Learning is essential reading for students, developers, or anyone with a keen interest in taking their coding skills to the next level.

Nasopharyngeal Carcinoma: From Etiology to Clinical Practice discusses NPC from basic science, to clinical management through the perspective of members of the Centre for Nasopharyngeal Carcinoma Research in Hong Kong. It encompasses not only the most detailed information about multiple aspects of NPC, but also the modern day research model of scientist-clinician collaboration, focusing on bench-to-bedside approach. Basic science is covered, discussing genetics and genomics in NPC and its epidemiology and the role of Epstein-Barr Virus (EBV). Translational research is also covered, presenting topics such as animal models, plasma EBV DNA, molecular imaging and immunotherapy, amongst other topics. This book is a valuable source for cancer researchers, oncologists, medical oncologists and several members of the biomedical field who are interested in learning more about NPC management from both clinical and research perspectives.

Nasopharyngeal Cancer - Multidisciplinary Management provides a comprehensive account of the current state of knowledge on nasopharyngeal cancer and its multidisciplinary management. The first ten chapters document contain essential background information on subjects such as epidemiology, pathogenesis, molecular biology, pathology, and the use of imaging in diagnosis and staging. Subsequently, the various treatment options and combinations in a range of settings are examined in depth. Detailed attention is given to the roles of concurrent, adjuvant, and neoadjuvant chemotherapy and advanced radiotherapy techniques. Further chapters then explore surgical treatment, follow-up, treatment of metastatic disease, treatment-related complications, and nasopharyngeal cancer in children. This is an important book that will prove essential reading for the radiation oncology community worldwide and meet the need for substantial improvements in knowledge of modern techniques.