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Machine Learning, Animated

by Mark Liu

~~106,79€~~ 96,11€ 10% OFF

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 The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. This book eases you into basic ML concepts and summarises the learning process in three words: initialize, adjust and repeat.
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Data Science And Machine Learning - Mathematical And Statistical Methods, Second Edition

by Dirk P. Kroese, Thomas Taimre e Zdravko (University Of New South Wales) Botev

~~106,79€~~ 96,11€ 10% OFF

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 The purpose of Data Science and Machine Learning: Mathematical and Statistical Methods is to provide an accessible, yet comprehensive textbook intended for students interested in gaining a better understanding of the mathematics and statistics that underpin rich variety of ideas and machine learning algorithms in data science.
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Concise Introduction To Machine Learning

by A.C. Faul

~~68,89€~~ 62,00€ 10% OFF

 A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles and illustrates every concept using examples in both Python and MATLABÂ®, which are available on GitHub and can be run from there in Binder in a web browser.
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Multilinear Subspace Learning - Dimensionality Reduction Of Multidimensional Data

by Anastasios Venetsanopoulos, Haiping Lu e Konstantinos N. Plataniotis

74,19€ + 10% CARD

 Due to advances in sensor, storage, and networking technologies, data is being generated on a daily basis at an ever-increasing pace in a wide range of applications, including cloud computing, mobile Internet, and medical imaging. This large multidimensional data requires more efficient dimensionality reduction schemes than the traditional techniqu
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Multi-Label Dimensionality Reduction

by Jieping Ye, Liang Sun e Shuiwang Ji

74,19€ + 10% CARD

 Suitable for researchers in machine learning, data mining, and computer vision, this book presents discussions on algorithms and applications for dimensionality reduction. It covers models for general dimensionality reduction in multi-label classification. It also presents a novel framework to unify a variety of models.
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Ensemble Methods - Foundations And Algorithms

by Zhi-Hua Zhou

~~63,59€~~ 57,23€ 10% OFF

 Ensemble methods that train multiple learners and then combine them to use, with Boosting and Bagging as representatives, are well-known machine learning approaches. It has become common sense that an ensemble is usually significantly more accurate than a single learner, and ensemble methods have already achieved great success in various real-world tasks.Twelve years have passed since the publication of the first edition of the book in 2012 (Japanese and Chinese versions published in 2017 and 2020, respectively). Many significant advances in this field have been developed. First, many theoretical issues have been tackled, for example, the fundamental question of why AdaBoost seems resistant to overfitting gets addressed, so that now we understand much more about the essence of ensemble methods. Second, ensemble methods have been well developed in more machine learning fields, e.g., isolation forest in anomaly detection, so that now we have powerful ensemble methods for tasks beyond conventional supervised learning.Third, ensemble mechanisms have also been found helpful in emerging areas such as deep learning and online learning. This edition expands on the previous one with additional content to reflect the significant advances in the field, and is written in a concise but comprehensive style to be approachable to readers new to the subject.
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Computational Trust Models And Machine Learning

63,59€ + 10% CARD

 Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:Explains
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Handbook Of Natural Language Processing

74,19€ + 10% CARD

 The Handbook of Natural Language Processing, Second Edition presents practical tools and techniques for implementing natural language processing in computer systems. Along with removing outdated material, this edition updates every chapter and expands the content to include emerging areas, such as sentiment analysis.New to the Second EditionGreater
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Sparse Modeling - Theory, Algorithms, And Applications

by Genady Grabarnik e Irina Rish

63,59€ + 10% CARD

 Sparse models are particularly useful in scientific applications, such as biomarker discovery in genetic or neuroimaging data, where the interpretability of a predictive model is essential. Sparsity can also dramatically improve the cost efficiency of signal processing.Sparse Modeling: Theory, Algorithms, and Applications provides an introduction t
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Entropy Randomization In Machine Learning

by Alexey Yu. Popkov, Yuri A. Dubnov e Yuri S. Popkov

~~63,53€~~ 57,18€ 10% OFF

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 Entropy Randomization in Machine Learning presents a new approach to machine learning - entropy randomization - to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).
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Regularization, Optimization, Kernels, And Support Vector Machines

63,59€ + 10% CARD

 Featuring contributions from leading experts, this volume provides an up-to-date look at large-scale machine learning. It comprehensively covers the latest research and advances in regularization, sparsity, and compressed sensing; convex and large-scale optimization; and kernel methods and SVMs.
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Statistical Reinforcement Learning - Modern Machine Learning Approaches

by Masashi Sugiyama

63,59€ + 10% CARD

 Reinforcement learning (RL) is a framework for decision making in unknown environments based on a large amount of data. Several practical RL applications for business intelligence, plant control, and gaming have been successfully explored in recent years. Providing an accessible introduction to the field, this book covers model-based and model-free approaches, policy iteration, and policy search methods. It presents illustrative examples and state-of-the-art results, including dimensionality reduction in RL and risk-sensitive RL. The book provides a bridge between RL and data mining and machine learning research.
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Bayesian Programming

by Emmanuel Mazer, Juan Ahuactzin, Kamel Mekhnacha e Pierre Bessiere

52,99€ + 10% CARD

 A new modeling methodology, new inference algorithms, new programming languages, and new hardware are all needed to create a complete Bayesian computing framework. Focusing on the methodology and algorithms, this book describes the first steps toward reaching that goal. It emphasizes probability as an alternative to Boolean logic, covering new methods to build probabilistic programs for real-world applications. The book encourages readers to explore emerging areas and develop new programming languages and hardware architectures. A Python package is available on a supplementary website.
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Deep And Shallow - Machine Learning In Music And Audio

by Ross Greer e Shlomo Dubnov

~~64,91€~~ 58,42€ 10% OFF

 Combining signals and language models in one place, this book explores how sound may be represented and manipulated by computer systems, and how our devices may come to recognize particular sonic patterns as musically meaningful or creative through the lens of information theory.
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Machine Learning, Animated

by Mark Liu

104,66€ + 10% CARD

 The release of ChatGPT has kicked off an arms race in Machine Learning (ML), however ML has also been described as a black box and very hard to understand. This book eases you into basic ML concepts and summarises the learning process in three words: initialize, adjust and repeat.
ENGLISH

Pragmatic Programmer For Machine Learning - Engineering Analytics And Data Science Solutions

by Marco Scutari e Mauro Malvestio

63,59€ + 10% CARD

 Machine learning has redefined the way we work with data and is increasingly becoming an indispensable part of everyday life, yet software engineering has played a remarkably small role compared to other disciplines. This book addresses such a disparity.
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Bayesian Programming

by Emmanuel (Cnrs, Grenoble, France) Mazer, Juan Ahuactzin, Kamel (Probayes Inc., Montbonnot, France) Mekhnacha e Pierre Bessiere

66,23€ + 10% CARD

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 A new modeling methodology, new inference algorithms, new programming languages, and new hardware are all needed to create a complete Bayesian computing framework. Focusing on the methodology and algorithms, this book describes the first steps toward reaching that goal. It emphasizes probability as an alternative to Boolean logic, covering new m
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Introduction To Machine Learning With Applications In Information Security

by Mark Stamp

63,59€ + 10% CARD

 Introduction to Machine Learning with Applications in Information Security, Second Edition provides a classroom-tested introduction to a wide variety of machine learning and deep learning algorithms and techniques, reinforced via realistic applications.
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Entropy Randomization In Machine Learning

by Alexey Yu. Popkov, Yuri A. Dubnov e Yuri S. Popkov

62,26€ + 10% CARD

 Entropy Randomization in Machine Learning presents a new approach to machine learning - entropy randomization - to obtain optimal solutions under uncertainty (uncertain data and models of the objects under study).
ENGLISH

Transformers For Machine Learning - A Deep Dive

by Kenneth Graham, Uday Kamath e Wael Emara

63,59€ + 10% CARD

 Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. This is the first comprehensive book on transformers.
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Artificial Intelligence And Causal Inference

by Momiao Xiong

63,59€ + 10% CARD

 Artificial Intelligence and Causal Inference address the recent development of relationships between artificial intelligence (AI) and causal inference. Despite significant progress in AI, a great challenge in AI development we are still facing is to understand mechanism underlying intelligence, including reasoning, planning and imagination.
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Sparse Modeling - Theory, Algorithms, And Applications

by Genady Grabarnik e Irina Rish

64,88€ + 10% CARD

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 This book provides an introduction to the growing field of sparse modeling, including application examples, problem formulations that yield sparse solutions, algorithms for finding such solutions, and recent theoretical results on sparse recovery. It describes optimization problems involving commonly used sparsity-enforcing approaches as well as
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A First Course In Machine Learning

by Mark Girolami e Simon Rogers

62,18€ + 10% CARD

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 The new edition of this popular, undergraduate textbook has been revised and updated to reflect current growth areas in Machine Learning. The new edition includes three new chapters with more detailed discussion of Markov Chain Monte Carlo techniques, Classification and Regression with Gaussian Processes, and Dirichlet Process models.
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Transformers For Machine Learning - A Deep Dive

by Kenneth Graham, Uday Kamath e Wael Emara

155,47€ + 10% CARD

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 Transformers are becoming a core part of many neural network architectures, employed in a wide range of applications such as NLP, Speech Recognition, Time Series, and Computer Vision. Transformers have gone through many adaptations and alterations, resulting in newer techniques and methods. This is the first comprehensive book on transformers.
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