Machine learning

Use TensorFlow 2.

This book provides an in-depth discussion of challenges encountered in deploying real-life large-scale systems and the state-of-the-art solutions in personalization.

This book constitutes the refereed proceedings of the 10th European Conference on Artificial Intelligence in Music, Sound, Art and Design, EvoMUSART 2021, held as part of Evo* 2021, as Virtual Event, in April 2021, co-located with the Evo* 2021 events, EvoCOP, EvoApplications, and EuroGP.

MACHINE LEARNING TECHNIQUES AND ANALYTICS FOR CLOUD SECURITY This book covers new methods, surveys, case studies, and policy with almost all machine learning techniques and analytics for cloud security solutions The aim of Machine Learning Techniques and Analytics for Cloud Security is to integrate machine learning approaches to meet various analytical issues in cloud security.

Explore the multidisciplinary nature of complex networks through machine learning techniques Statistical and Machine Learning Approaches for Network Analysis provides an accessible framework for structurally analyzing graphs by bringing together known and novel approaches on graph classes and graph measures for classification.

This element introduces machine learning (ML) tools that can help asset managers discover economic and financial theories.

This book offers an introduction into quantum machine learning research, covering approaches that range from "e;near-term"e; to fault-tolerant quantum machine learning algorithms, and from theoretical to practical techniques that help us understand how quantum computers can learn from data.

INTERNET OF HEALTHCARE THINGS The book addresses privacy and security issues providing solutions through authentication and authorization mechanisms, blockchain, fog computing, machine learning algorithms, so that machine learning-enabled IoT devices can deliver information concealed in data for fast, computerized responses and enhanced decision-making.

This book provides an overview of the Internet of Things Network and Machine Learning and introduces Internet of Things architecture.

The burgeoning field of data analysis is expanding at an incredible pace due to the proliferation of data collection in almost every area of science.

Large language models (LLMs) are not just shaping the trajectory of AI, they're also unveiling a new era of security challenges.

This two-volume set LNCS 12918 - 12919 constitutes the refereed proceedings of the 23nd International Conference on Information and Communications Security, ICICS 2021, held in Chongqing, China, in September 2021.

This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning.

This book covers the essential concepts and strategies within traditional and cutting-edge feature learning methods thru both theoretical analysis and case studies.

Covers text mining and link detection algorithms, pre-processing techniques, knowledge representation, visualization and applications.

The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020.

This book constitutes revised and selected papers from the scientific satellite events held in conjunction with the18th International Conference on Service-Oriented Computing, ICSOC 2020.

This book constitutes the proceedings of the 5th International Conference on Smart Computing and Communication, SmartCom 2020, which took place in Paris, France, during December 29-31, 2020.

Design and use machine learning models for music generation using Magenta and make them interact with existing music creation toolsKey FeaturesLearn how machine learning, deep learning, and reinforcement learning are used in music generationGenerate new content by manipulating the source data using Magenta utilities, and train machine learning models with itExplore various Magenta projects such as Magenta Studio, MusicVAE, and NSynthBook DescriptionThe importance of machine learning (ML) in art is growing at a rapid pace due to recent advancements in the field, and Magenta is at the forefront of this innovation.

100 recipes that teach you how to perform various machine learning tasks in the real worldAbout This BookUnderstand which algorithms to use in a given context with the help of this exciting recipe-based guideLearn about perceptrons and see how they are used to build neural networksStuck while making sense of images, text, speech, and real estate?

Learn how to harness modern deep-learning methods in many contexts.

THIS ISN'T AN EPISODE OF BLACK MIRROR.

Disruption resulting from the proliferation of AI is coming.

MemComputing is a new computing paradigm that employs time non-locality (memory) to both process and store information.

Unsupervised domain adaptation (UDA) is a challenging problem in machine learning where the model is trained on a source domain with labeled data and tested on a target domain with unlabeled data.

This book is the first comprehensive guide to the intersection of data governance and machine learning (ML) projects.

The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation.

Search has been vital to artificial intelligence from the very beginning as a core technique in problem solving.

This book introduces zero-effort technologies (ZETs), an emerging class of technologies that require little or no effort from the people who use them.

It is undeniable that the recent revival of artificial intelligence (AI) has significantly changed the landscape of science in many application domains, ranging from health to defense and from conversational interfaces to autonomous cars.

Get hands-on with the browser-based JavaScript library for training and deploying machine learning models effectivelyKey FeaturesBuild, train and run machine learning models in the browser using TensorFlow.

RDF-based knowledge graphs require additional formalisms to be fully context-aware, which is presented in this book.

Artificial intelligent systems, which offer great improvement in healthcare sector assisted by machine learning, wireless communications, data analytics, cognitive computing, and mobile computing provide more intelligent and convenient solutions and services.

Welcome to your hands-on guide to artificial intelligence for IT operations (AIOps).

This Synthesis Lecture focuses on techniques for efficient data orchestration within DNN accelerators.

Your one-stop guide to learning and implementing artificial neural networks with Keras effectivelyKey FeaturesDesign and create neural network architectures on different domains using KerasIntegrate neural network models in your applications using this highly practical guideGet ready for the future of neural networks through transfer learning and predicting multi network modelsBook DescriptionNeural networks are used to solve a wide range of problems in different areas of AI and deep learning.

This book constitutes the proceedings of the International Workshop on Shape in Medical Imaging, ShapeMI 2020, which was held in conjunction with the 23rd International Conference on Medical Image Computing and Computer Assistend Intervention, MICCAI 2020, in October 2020.

This thesis represents one of the most comprehensive and in-depth studies of the use of Lorentz-boosted hadronic final state systems in the search for signals of Supersymmetry conducted to date at the Large Hadron Collider.

This book represents a selection of papers presented at the Inductive Logic Programming (ILP) workshop held at Cumberland Lodge, Great Windsor Park.

Explore Generative AI and understand its key concepts, architecture, and tangible business use cases.

This book constitutes the proceedings of the international workshops co-located with the 16th International Conference on Document Analysis and Recognition, ICDAR 2021, held in Lausanne, Switzerland, in September 2021.

This is the first book completely dedicated to positioning and navigation using machine learning methods.

This is the first study of Boko Haram that brings advanced data-driven, machine learning models to both learn models capable of predicting a wide range of attacks carried out by Boko Haram, as well as develop data-driven policies to shape Boko Haram's behavior and reduce attacks by them.

This book presents the recent advances including tools and techniques in the constantly changing landscape of machine learning (ML).

This book offers a comprehensive introduction to the central ideas that underpin deep learning.

If you're training a machine learning model but aren't sure how to put it into production, this book will get you there.