Machine learning

This book constitutes the proceedings of the 5th International Conference on Lean and Agile Software Development, LASD 2021, which was held online on January 23, 2021.

Artificial Intelligence and Edge Computing for Sustainable Ocean Health explores the transformative role of AI and edge computing in preserving and enhancing ocean health.

Dive into hyperparameter tuning of machine learning models and focus on what hyperparameters are and how they work.

This book constitutes the thoroughly refereed proceedings of the 5th International Conference on Information and Knowledge Systems, ICIKS 2021, which was held online during June 22-23, 2021.

A remarkable facet of the human brain is its ability to manage multiple tasks with apparent simultaneity.

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.

Making use of data is not anymore a niche project but central to almost every project.

Build and deploy machine learning and deep learning models in production with end-to-end examples.

Work through exciting projects to explore the capabilities of Go and Machine LearningKey FeaturesExplore ML tasks and Go's machine learning ecosystemImplement clustering, regression, classification, and neural networks with GoGet to grips with libraries such as Gorgonia, Gonum, and GoCv for training models in GoBook DescriptionGo is the perfect language for machine learning; it helps to clearly describe complex algorithms, and also helps developers to understand how to run efficient optimized code.

This book describes theoretical advances in the study of artificial neural networks.

Master the math needed to excel in data science, machine learning, and statistics.

Contemporary research in science and engineering is seeking to harness the versatility and sustainability of living organisms.

Artificial intelligence (AI) is revolutionizing our daily lives, thanks to remarkable advancements in research and the widespread adoption of interactive technologies.

The two-volume set LNCS 12765-12766 constitutes the refereed proceedings of the thematic area Human Interface and the Management of Information, HIMI 2021, which was held as part of HCI International 2021 and took place virtually during July 24-29, 2021.

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.

The authors develop a malware fingerprinting framework to cover accurate android malware detection and family attribution in this book.

How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy.

This book constitutes the refereed joint proceedings of the 4th International Workshop on Interpretability of Machine Intelligence in Medical Image Computing, iMIMIC 2020, and the First International Workshop on Topological Data Analysis and Its Applications for Medical Data, TDA4MedicalData 2021, held on September 27, 2021, in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021.

This book is a collection of peer-reviewed best selected research papers presented at the Fifth International Conference on Advances in Distributed Computing and Machine Learning (ICADCML 2024), organized by School of Electronics and Engineering, VIT - AP University, Amaravati, Andhra Pradesh, India, during 5-6 January 2024.

This modern approach integrates classical and contemporary methods, fusing theory and practice and bridging the gap to statistical learning.

Covering the fundamentals of kernel-based learning theory, this is an essential resource for graduate students and professionals in computer science.

The world stands at a pivotal moment due to the emergence of Generative AI, specifically ChatGPT.

Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as TensorFlow 2 and Keras.

Sure to be influential, this book lays the foundations for the use of algebraic geometry in statistical learning theory.

Learn how to use R to apply powerful machine learning methods and gain insight into real-world applications using clustering, logistic regressions, random forests, support vector machine, and more.

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning.

This book demonstrates the optimal adversarial attacks against several important signal processing algorithms.

This book focuses on the deep learning technologies and their applications in the catenary detection of high-speed railways.

This interdisciplinary book incorporates various aspects of environment, ecology, and natural disaster management including cognitive informatics and computing.

Covering the fundamentals of kernel-based learning theory, this is an essential resource for graduate students and professionals in computer science.

This book constitutes the refereed proceedings of the 14th International Conference on Cognitive Radio-Oriented Wireless Networks, CROWNCOM 2019, held in Poznan, Poland, in June 2019.

This handbook covers a wide range of topics related to the collection, processing, analysis, and use of geospatial data in their various forms.

This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks.

Defines the notion of an activity model learned from sensor data and presents key algorithms that form the core of the field Activity Learning: Discovering, Recognizing and Predicting Human Behavior from Sensor Data provides an in-depth look at computational approaches to activity learning from sensor data.

In a VUCA world, which is becoming increasingly volatile, uncertain, and complex, companies, organizations, and states must respond promptly and adequately to the respective situations.

An accessible synthesis of ethical issues raised by artificial intelligence that moves beyond hype and nightmare scenarios to address concrete questions.

Develop generative models for a variety of real-world use-cases and deploy them to productionKey FeaturesDiscover various GAN architectures using Python and Keras libraryUnderstand how GAN models function with the help of theoretical and practical examplesApply your learnings to become an active contributor to open source GAN applicationsBook DescriptionGenerative Adversarial Networks (GANs) have revolutionized the fields of machine learning and deep learning.

This integrated collection covers a range of parallelization platforms, concurrent programming frameworks and machine learning settings, with case studies.

This guide covers the fundamental technical principles and various business applications of Generative AI for planning, developing, and evaluating AI-driven products.

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.

Roughly inspired by the human brain, deep neural networks trained with large amounts of data can solve complex tasks with unprecedented accuracy.

This book is meant as a textbook for undergraduate and graduate students who are willing to understand essential elements of machine learning from both a theoretical and a practical perspective.

Gain the confidence you need to apply machine learning in your daily work.

This book constitutes the refereed proceedings of the 16th International Colloquium on Theoretical Aspects of Computing, ICTAC 2019, held in Hammamet, Tunisia, in October/November 2019.

This integrated introduction to fundamentals, computation, and software is your key to understanding and using advanced Bayesian methods.

Data mining is often referred to by real-time users and software solutions providers as knowledge discovery in databases (KDD).

An interdisciplinary framework for learning methodologies covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data.

This book is intended to present the state of the art in research on machine learning and big data analytics.