Skip to main content
Search Button
Canada Kobo store Gift Cards Help

Rakuten Kobo

Wishlist

Shopping Cart

You're getting the VIP treatment!

Item(s) unavailable for purchase
Please review your cart. You can remove the unavailable item(s) now or we'll automatically remove it at Checkout.
itemsitem
itemsitem

Recommended For You

Loading...


Showing 1 - 12 of 12 results for “takashi ishida”
Skip side bar filters

  • Machine Learning from Weak Supervision

    An Empirical Risk Minimization Approach

    by Masashi Sugiyama, Han Bao, Takashi Ishida, Nan Lu, Tomoya Sakai ...
    Series series Adaptive Computation and Machine Learning series
    Fundamental theory and practical algorithms of weakly supervised classification, emphasizing an approach based on empirical risk minimization.Standard machine learning techniques require large amounts of labeled data to work well. When we apply machine learning to problems in the physical world, however, it is extremely difficult to collect such quantities of labeled data. In this book Masashi ... Read more

    $67.99 CAD

People who read this also enjoyed

  • Causal Inference in Statistics

    A Primer

    by Judea Pearl, Madelyn Glymour, Nicholas P. Jewell ...
    CAUSAL INFERENCE IN STATISTICSA PrimerCausality is central to the understanding and use of data. Without an understanding of cause–effect relationships, we cannot use data to answer questions as basic as "Does this treatment harm or help patients?" But though hundreds of introductory texts are available on statistical methods of data analysis, until now, no beginner-level book has been written ... Read more

    $53.99 CAD

  • Computer Age Statistical Inference

    Algorithms, Evidence, and Data Science

    by Bradley Efron, Trevor Hastie ...
    Series Book 5 - Institute of Mathematical Statistics Monographs
    The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and in influence. 'Big data', 'data science', and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? This book takes us on an exhilarating ... Read more

    $81.99 CAD

  • Artificial Intelligence

    With an Introduction to Machine Learning, Second Edition

    by Richard E. Neapolitan, Xia Jiang ...
    Series series Chapman & Hall/CRC Artificial Intelligence and Robotics Series
    The first edition of this popular textbook, Contemporary Artificial Intelligence, provided an accessible and student friendly introduction to AI. This fully revised and expanded update, Artificial Intelligence: With an Introduction to Machine Learning, Second Edition, retains the same accessibility and problem-solving approach, while providing new material and methods.The book is divided into five ... Read more

    $88.99 CAD

  • Markov Models: An Introduction to Markov Models

    by Steven Taylor ...
    Markov ModelsThis book will offer you an insight into the Hidden Markov Models as well as the Bayesian Networks. Additionally, by reading this book, you will also learn algorithms such as Markov Chain Sampling.Furthermore, this book will also teach you how Markov Models are very relevant when a decision problem is associated with a risk that continues over time, when the timing of occurrenc... ... Read more

    $5.99 CAD or Free with Kobo Plus

  • Elements of Causal Inference

    Foundations and Learning Algorithms

    by Jonas Peters, Dominik Janzing, Bernhard Scholkopf ...
    Series series Adaptive Computation and Machine Learning series
    A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning.The mathematization of causality is a relatively recent development, and has become increasingly important in data science and machine learning. This book offers a self-contained and concise introduction to causal models and how to learn them from data.After explaining the ... Read more

    $51.99 CAD

  • Statistical Relational Artificial Intelligence

    Logic, Probability, and Computation

    by Kristian Kersting, Luc De Raedt, Sriraam Natarajan, David Poole ...
    Series series Synthesis Lectures on Artificial Intelligence and Machine Learning
    An intelligent agent interacting with the real world will encounter individual people, courses, test results, drugs prescriptions, chairs, boxes, etc., and needs to reason about properties of these individuals and relations among them as well as cope with uncertainty. Uncertainty has been studied in probability theory and graphical models, and relations have been studied in logic, in particular in ... Read more

    $58.99 CAD

  • Neural Network Methods in Natural Language Processing

    by Yoav Goldberg, Graeme Hirst ...
    Series series Synthesis Lectures on Human Language Technologies
    Neural networks are a family of powerful machine learning models and this book focuses on their application to natural language data.The first half of the book (Parts I and II) covers the basics of supervised machine learning and feed-forward neural networks, the basics of working with machine learning over language data, and the use of vector-based rather than symbolic representations for words. ... Read more

    $67.99 CAD

  • Experimental Design

    Procedures for the Behavioral Sciences

    by Roger E. Kirk ...
    This classic text, with a reputuation for accessibility and readability, has been revised and updated to make learning design concepts even easier. Roger E. Kirk shows how three simple experimental designs can be combined to form a variety of complex designs. He provides diagrams illustrating how subjects are assigned to treatments and treatment combinations. New terms are emphasized in boldface ... Read more

    $175.99 CAD

  • Statistical Learning for Biomedical Data

    by James D. Malley, Karen G. Malley, Sinisa Pajevic ...
    Series series Practical Guides to Biostatistics and Epidemiology
    This book is for anyone who has biomedical data and needs to identify variables that predict an outcome, for two-group outcomes such as tumor/not-tumor, survival/death, or response from treatment. Statistical learning machines are ideally suited to these types of prediction problems, especially if the variables being studied may not meet the assumptions of traditional techniques. Learning machines ... Read more

    $52.99 CAD

  • Fuzzy Sets and Systems

    Theory and Applications

    by Didier J. Dubois ...
    Fuzzy Sets and Systems: Theory and Applications provides a comprehensive research monography that cover all of the important developments in the theory of fuzzy sets and their applications that have taken place during the past several years. ... Read more

    $64.79 CAD

  • Data Processing for the AHP/ANP

    by Daji Ergu, Yong Shi, Gang Kou, Yi Peng ...
    Series series Business and Management (R0)
    The positive reciprocal pairwise comparison matrix (PCM) is one of the key components which is used to quantify the qualitative and/or intangible attributes into measurable quantities. This book examines six understudied issues of PCM, i.e. consistency test, inconsistent data identification and adjustment, data collection, missing or uncertain data estimation, and sensitivity analysis of rank ... Read more

    $64.99 CAD