Machine Theory

The goal of Optimal Transport (OT) is to define geometric tools that are useful to compare probability distributions. Their use dates back to 1781.Recent years have witnessed a new revolution in the spread of OT, thanks to the emergence of approximate...

Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing an appropriate...

Introduction to Machine Learning with Applications in Information Security provides a class-tested introduction to a wide variety of machine learning algorithms, reinforced through realistic applications. The book is accessible and doesn't prove...

This textbook is a comprehensive introduction to computational mathematics and scientific computing suitable for undergraduate and postgraduate courses. It presents both practical and theoretical aspects of the subject, as well as advantages and pitfalls...

In the midst of the fourth industrial revolution, big data is weighed in gold, placing enormous power in the hands of data scientists - the modern AI alchemists. But great power comes with greater responsibility. This book seeks to shape, in a practical,...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9788119177486Author Mei WongFormat PaperbackPage Count 178Imprint GitforgitsPublisher GitforgitsWeight(grams) 318g

Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from...

The twenty last years have been marked by an increase in available data and computing power. In parallel to this trend, the focus of neural network research and the practice of training neural networks has undergone a number of important changes, for...

Grasp machine learning concepts, techniques, and algorithms with the help of real-world examples using Python libraries such as TensorFlow and scikit-learn Key Features Exploit the power of Python to explore the world of data mining and data analytics...

Leverage the power of reward-based training for your deep learning models with Python Key Features Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) Study practical deep reinforcement learning using Q-Networks...

Black-box machine learning models are now routinely used in high-risk settings, like medical diagnostics, which demand uncertainty quantification to avoid consequential model failures. Conformal prediction is a user-friendly paradigm for creating...

Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabilities of the Amazon Web Services ecosystem and provides...

A unified view of metaheuristics This book provides a complete background on metaheuristics and shows readers how to design and implement efficient algorithms to solve complex optimization problems across a diverse range of applications, from networking...

Leverage the power of Java and its associated machine learning libraries to build powerful predictive modelsKey FeaturesSolve predictive modeling problems using the most popular machine learning Java libraries Explore data processing, machine learning,...

By the year 2020, the basic memory components of a computer will be the size of individual atoms. At such scales, the current theory of computation will become invalid. "Quantum computing" is reinventing the foundations of computer science and...

The formalism of probabilistic graphical models provides a unifying framework for capturing complex dependencies among random variables, and building large-scale multivariate statistical models. Graphical models have become a focus of research in many...

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...

Physical and behavioral biometric technologies such as fingerprinting, facial recognition, voice identification, etc. have enhanced the level of security substantially in recent years. Governments and corporates have employed these technologies to...

"Automated scoring engines [...] require a careful balancing of the contributions of technology, NLP, psychometrics, artificial intelligence, and the learning sciences. The present handbook is evidence that the theories, methodologies, and underlying...

In this monograph, the authors present an introduction to the framework of variational autoencoders (VAEs) that provides a principled method for jointly learning deep latent-variable models and corresponding inference models using stochastic gradient...

Interest in predictive analytics of big data has grown exponentially in the four years since the publication of Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. In the third...

The 4-volume set LNCS constitutes the main proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7–9, 2025. The 64 full papers and 52 short papers presented in these...

The 4-volume set LNCS constitutes the main proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7–9, 2025. The 64 full papers and 52 short papers presented in these...

The 4-volume set LNCS constitutes the main proceedings of the 25th International Conference on Computational Science, ICCS 2025, which took place in Singapore, Singapore, during July 7–9, 2025. The 64 full papers and 52 short papers presented in these...

This Festschrift celebrates the career of Vivek Sarkar, a pioneer who has influenced research into programming languages, compilers, runtime systems, and debugging and verification systems for high-performance computers. After foundational Ph.D. work at...

This book constitutes the refereed proceedings of the 21st Conference on Computability and Logic, CiE 2025, held in Lisbon, Portugal, during July 14–18, 2025. The 27 full papers included in this book were carefully reviewed and selected from 49...

Together with the companion volume by the same author, Operators, Functions, and Systems: An Easy Reading. Volume 2: Model Operators and Systems, Mathematical Surveys and Monographs, Vol. 93, AMS, 2002, this unique work combines four major topics of...

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9789355510716Author Dr Varsha H PatilFormat PaperbackPage Count 622Imprint Bpb PublicationsPublisher Bpb PublicationsWeight(grams) 1052g

Apologies but we at Booksplease don't have a full description for this book.Book InformationISBN 9781638284543Author George H. ChenFormat PaperbackPage Count 192Imprint now publishers IncPublisher now publishers IncWeight(grams) 278g

The book comprises original articles on topical issues of risk theory, rational decision making, statistical decisions, and control of stochastic systems. The articles are the outcome of a series international projects involving the leading scholars in...

If you have basic knowledge of R, in terms of its libraries, and are aware of different machine learning techniques, this book is for you. Those with experience in data analysis who are interested in mining social media data will also find this book...

This book provides insights into how to approach and utilise data science tools, technologies, and methodologies related to artificial intelligence (AI) in industrial contexts. It explains the essence of distributed computing and AI technologies and...

This book highlights the importance of data-driven techniques to solve wireless communication problems. It presents a number of problems (e.g., related to performance, security, and social networking), and provides solutions using various data-driven...

A hands-on guide for professionals to perform various data science tasks in R Key Features Explore the popular R packages for data science Use R for efficient data mining, text analytics and feature engineering Become a thorough data science professional...

Explore the power of Generative Adversarial Networks to empower your business About This Book * Use different datasets to build advanced projects in Generative Adversarial Networks domain *Implementing projects ranging from generating 3D shapes to Face...

Develop generative models for a variety of real-world use-cases and deploy them to production Key Features Discover various GAN architectures using Python and Keras library Understand how GAN models function with the help of theoretical and practical...

Deploy supervised and unsupervised machine learning algorithms using scikit-learn to perform classification, regression, and clustering.Key FeaturesBuild your first machine learning model using scikit-learnTrain supervised and unsupervised models using...

Handbook of Artificial Intelligence in Biomedical Engineering focuses on recent AI technologies and applications that provide some very promising solutions and enhanced technology in the biomedical field. Recent advancements in computational techniques,...

Supervised and unsupervised machine learning made easy in Scala with this quick-start guide. Key Features Construct and deploy machine learning systems that learn from your data and give accurate predictions Unleash the power of Spark ML along with...

Computer vision-based crack-like object detection has many useful applications, such as inspecting/monitoring pavement surface, underground pipeline, bridge cracks, railway tracks etc. However, in most contexts, cracks appear as thin, irregular...