A world first “health focused" flexible program that is going to change the way you see and attain your health and fitness goals. This is a DIY program designed for both men and women to achieve the bodies they want by following simple self-care foundations on a daily basis. You can complete the program in the comfort of your own home, in your own time, and without the need of expensive equipment, gym access, designer sportswear or any other restriction.

It is essential to have a daily routine that you can follow. Nutrition and exercise are essential elements of a daily routine for wellness and your mental health.

Learn how to build machine translation systems with deep learning from the ground up, from basic concepts to cutting-edge research.

IRON GATES is a sci-fi horror / post-apocalyptic novel, detailing a bleak view of the spiritual horrors of the world-to-come. Set seventy years after a worldwide nuclear conflagration, IRON GATES allows the reader a sight into a nightmarish landscape populated by even more nightmarish characters in a hideous future which leaves little to the imagination. Brutal and unsparing, it is not suitable for readers under 18. Readers should be advised of extreme graphic content.

The natural interaction ability between human and machine mainly involves human-machine dialogue ability, multi-modal sentiment analysis ability, human-machine cooperation ability, and so on. To enable intelligent computers to have multi-modal sentiment analysis ability, it is necessary to equip them with a strong multi-modal sentiment analysis ability during the process of human-computer interaction. This is one of the key technologies for efficient and intelligent human-computer interaction. This book focuses on the research and practical applications of multi-modal sentiment analysis for human-computer natural interaction, particularly in the areas of multi-modal information feature representation, feature fusion, and sentiment classification. Multi-modal sentiment analysis for natural interaction is a comprehensive research field that involves the integration of natural language processing, computer vision, machine learning, pattern recognition, algorithm, robot intelligent system, human-computer interaction, etc. Currently, research on multi-modal sentiment analysis in natural interaction is developing rapidly. This book can be used as a professional textbook in the fields of natural interaction, intelligent question answering (customer service), natural language processing, human-computer interaction, etc. It can also serve as an important reference book for the development of systems and products in intelligent robots, natural language processing, human-computer interaction, and related fields.

Dependency-based methods for syntactic parsing have become increasingly popular in natural language processing in recent years. This book gives a thorough introduction to the methods that are most widely used today. After an introduction to dependency grammar and dependency parsing, followed by a formal characterization of the dependency parsing problem, the book surveys the three major classes of parsing models that are in current use: transition-based, graph-based, and grammar-based models. It continues with a chapter on evaluation and one on the comparison of different methods, and it closes with a few words on current trends and future prospects of dependency parsing. The book presupposes a knowledge of basic concepts in linguistics and computer science, as well as some knowledge of parsing methods for constituency-based representations. Table of Contents: Introduction / Dependency Parsing / Transition-Based Parsing / Graph-Based Parsing / Grammar-Based Parsing / Evaluation / Comparison / Final Thoughts

In recent years, a large number of explainable recommendation approaches have been proposed and applied in real-world systems. This survey provides a comprehensive review of the explainable recommendation research.