Account
Orders
Advanced search
Based on the authors' extensive teaching experience, this hands-on graduate-level textbook teaches how to carry out large-scale data analytics and design machine learning solutions for big data. With a focus on fundamentals, this extensively class-tested textbook walks...
The book offers a succinct overview of the technical components of blockchain networks, also known as distributed digital ledger networks. Written from an academic perspective, it surveys ongoing research challenges as well as existing literature. Several chapters...
Online algorithms are a rich area of research with widespread applications in scheduling, combinatorial optimization, and resource allocation problems. This lucid textbook provides an easy but rigorous introduction to online algorithms for graduate and senior...
Privacy-preserving computing aims to protect the personal information of users while capitalizing on the possibilities unlocked by big data. This practical introduction for students, researchers, and industry practitioners is the first cohesive and systematic...
Cyberspace is essential for socializing, learning, shopping, and just about everything in modern life. Yet, there is also a dark side to cyberspace: sub-national, transnational, and international actors are challenging the ability of sovereign governments to provide a...
Virtual reality (VR) is a powerful technology that promises to transform our lives. This balanced and interdisciplinary text blends the key components from computer graphics, perceptual psychology, human physiology, behavioral science, media studies, human-computer...
Presenting the fundamental algorithms and data structures that power bioinformatics workflows, this book covers a range of topics from the foundations of sequence analysis (alignments and hidden Markov models) to classical index structures (k-mer indexes, suffix arrays,...
Learn about probability as it is used in computer science with this rigorous, yet highly accessible, undergraduate textbook. Fundamental probability concepts are explained in depth, prerequisite mathematics is summarized, and a wide range of computer science...
This concise and self-contained introduction builds up the spectral theory of graphs from scratch, with linear algebra and the theory of polynomials developed in the later parts. The book focuses on properties and bounds for the eigenvalues of the adjacency, Laplacian...
Distributional semantics develops theories and methods to represent the meaning of natural language expressions, with vectors encoding their statistical distribution in linguistic contexts. It is at once a theoretical model to express meaning, a practical methodology to...
Digital health translation is an important application of machine translation and multilingual technologies, and there is a growing need for accessibility in digital health translation design for disadvantaged communities. This book addresses that need by highlighting...
Through information theory, problems of communication and compression can be precisely modeled, formulated, and analyzed, and this information can be transformed by means of algorithms. Also, learning can be viewed as compression with side information. Aimed at students...
Robust statistics is the study of designing estimators that perform well even when the dataset significantly deviates from the idealized modeling assumptions, such as in the presence of model misspecification or adversarial outliers in the dataset. The classical...
Providing a logical framework for student learning, this is the first textbook on adversarial learning. It introduces vulnerabilities of deep learning, then demonstrates methods for defending against attacks and making AI generally more robust. To help students connect...
How do we know that climate change is an emergency?How did the scientific community reach this conclusion all but unanimously, and what tools did they use to do it? This book tells the story of climate models, tracing their history from nineteenth-century calculations...
The third edition of this practical introduction to Python has been thoroughly updated, with all code migrated to Jupyter notebooks.The notebooks are available online with executable versions of all of the book's content (and more).The text starts with a detailed...
This concise introduction provides an entry point to the world of inverse problems and data assimilation for advanced undergraduates and beginning graduate students in the mathematical sciences. It will also appeal to researchers in science and engineering who are...
String diagrams are powerful graphical methods for reasoning in elementary category theory. Written in an informal expository style, this book provides a self-contained introduction to these diagrammatic techniques, ideal for graduate students and researchers. Much of...
The mathematical theory of machine learning not only explains the current algorithms but can also motivate principled approaches for the future. This self-contained textbook introduces students and researchers of AI to the main mathematical techniques used to analyze...
Fully revised and updated, this third edition includes three new chapters on neural networks and deep learning including generative AI, causality, and the social, ethical and regulatory impacts of artificial intelligence. All parts have been updated with the methods...
Les livres numériques peuvent être téléchargés depuis l'ebookstore Numilog ou directement depuis une tablette ou smartphone.
PDF : format reprenant la maquette originale du livre ; lecture recommandée sur ordinateur et tablette EPUB : format de texte repositionnable ; lecture sur tous supports (ordinateur, tablette, smartphone, liseuse)
DRM Adobe LCP
LCP DRM Adobe
Sign up to get our latest ebook recommendations and special offers