Welcome to our book review site go-pdf.online!
You may have to Search all our reviewed books and magazines, click the sign up button below to create a free account.
Representation Learning
This monograph addresses advances in representation learning, a cutting-edge research area of machine learning. Representation learning refers to modern data transformation techniques that convert data of different modalities and complexity, including texts, graphs, and relations, into compact tabular representations, which effectively capture their semantic properties and relations. The monograph focuses on (i) propositionalization approaches, established in relational learning and inductive logic programming, and (ii) embedding approaches, which have gained popularity with recent advances in deep learning. The authors establish a unifying perspective on representation learning techniques developed in these various areas of modern data science, enabling the reader to understand the common underlying principles and to gain insight using selected examples and sample Python code. The monograph should be of interest to a wide audience, ranging from data scientists, machine learning researchers and students to developers, software engineers and industrial researchers interested in hands-on AI solutions.
Advance of Polymers Applied to Biomedical Applications: Cell Scaffolds
This book is a printed edition of the Special Issue "Advance of Polymers Applied to Biomedical Applications: Cell Scaffolds" that was published in Polymers
Trends in Stem Cell Proliferation and Cancer Research
The book will discuss the molecular mechanisms of cancer diseases, stem cell proliferation and transformation into cancer cells beyond the physiological processes that occur in normal stem cell biology. Some of the key oncogenic events in cancer and their signaling pathways that regulate cell division cycle progression will be described considering prospects for using such knowledge in advanced cancer therapy. Each chapter shall provide an invaluable resource for information on the most current advances in the field, with discussion of controversial issues and areas of emerging importance
Conquest of Body
This book reflects on the phenomenon of biotechnology and how it affects the body and discusses a number of related issues, including visualization, mediation, and epistemology. The author offers a compelling thesis, arguing that the exploration of the human body has one ultimate aim: to gain knowledge of it and to conquer it. Exploration of body has an intrinsic link to power, since knowledge is constitutive for the power over the body. Ultimately the conquest of body means the power to intervene into life processes. The book breaks new ground with its study of body visualizations, from the Renaissance drawings to the medical imaging. In particular, it investigates their complex mediality. It also considers the extension and the reach of biopower that is now possible thanks to a wide range of engineering applications. The author originally questions the research approach by rethinking the relationship between mental and sensual examination. She takes into consideration the epistemological problem of the two modes of exploration: obtaining knowledge from empirical exploration and projecting that knowledge to the object of exploration.
Exploiting Semantic Web Knowledge Graphs in Data Mining
Data Mining and Knowledge Discovery in Databases (KDD) is a research field concerned with deriving higher-level insights from data. The tasks performed in this field are knowledge intensive and can benefit from additional knowledge from various sources, so many approaches have been proposed that combine Semantic Web data with the data mining and knowledge discovery process. This book, Exploiting Semantic Web Knowledge Graphs in Data Mining, aims to show that Semantic Web knowledge graphs are useful for generating valuable data mining features that can be used in various data mining tasks. In Part I, Mining Semantic Web Knowledge Graphs, the author evaluates unsupervised feature generation st...
Bisociative Knowledge Discovery
Modern knowledge discovery methods enable users to discover complex patterns of various types in large information repositories. However, the underlying assumption has always been that the data to which the methods are applied to originates from one domain. The focus of this book, and the BISON project from which the contributions are originating, is a network based integration of various types of data repositories and the development of new ways to analyse and explore the resulting gigantic information networks. Instead of finding well defined global or local patterns they wanted to find domain bridging associations which are, by definition, not well defined since they will be especially interesting if they are sparse and have not been encountered before. The 32 contributions presented in this state-of-the-art volume together with a detailed introduction to the book are organized in topical sections on bisociation; representation and network creation; network analysis; exploration; and applications and evaluation.
Obracun
None
