Neural networks and fuzzy systems

Ontologies are formal knowledge representation methods that can provide means for a shared understanding of a given domain.

Applying artificial intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields.

This book delves into the critical realm of trust management within the Internet of Vehicles (IOV) networks, exploring its multifaceted implications on safety and security which forms part of the intelligent transportation system domain.

While many companies have already begun their journey towards high automation and AI-powered operations, the landscape continues to shift rapidly.

This book provides a comprehensive analysis of the tools and techniques used today for designing and modeling of efficient and robust swarm-intelligence based systems: highly (or fully) decentralized, semi-autonomous, highly-scalable infrastructures in various real-life scenarios.

Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practicesKey FeaturesBuild and refine LLMs step by step, covering data preparation, RAG, and fine-tuningLearn essential skills for deploying and monitoring LLMs, ensuring optimal performance in productionUtilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applicationsBook DescriptionArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution.

This book provides a comprehensive analysis of the tools and techniques used today for designing and modeling of efficient and robust swarm-intelligence based systems: highly (or fully) decentralized, semi-autonomous, highly-scalable infrastructures in various real-life scenarios.

The book emphasizes the role of data in driving healthcare transformation, providing readers with a roadmap for understanding and effectively implementing data-driven innovations.

A compact guide to mastering TensorFlow 2, covering essential APIs, datasets, and practical applications for efficient machine learning and deep learning projects.

A compact guide to mastering TensorFlow 2, covering essential APIs, datasets, and practical applications for efficient machine learning and deep learning projects.

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare.

The book emphasizes the role of data in driving healthcare transformation, providing readers with a roadmap for understanding and effectively implementing data-driven innovations.

This book introduces an auto design based optimization for building frames using an artificial neural network (ANN) based Lagrange method and novel genetic algorithm (GA).

Turn challenges into opportunities by learning advanced techniques for text generation, summarization, and question answering using LangChain and Google Cloud tools DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesSolve real-world business problems with hands-on examples of GenAI applications on Google CloudLearn repeatable design patterns for Gen AI on Google Cloud with a focus on architecture and AI ethicsBuild and implement GenAI agents and workflows, such as RAG and NL2SQL, using LangChain and Vertex AIPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionThe rapid transformation and enterprise adoption of GenAI has created an urgent demand for developers to quickly build and deploy AI applications that deliver real value.

This comprehensive guide addresses key challenges at the intersection of data science, graph learning, and privacy preservation.

This book introduces an auto design based optimization for building frames using an artificial neural network (ANN) based Lagrange method and novel genetic algorithm (GA).

While many companies have already begun their journey towards high automation and AI-powered operations, the landscape continues to shift rapidly.

This book provides a comprehensive exploration of generalization in deep learning, focusing on both theoretical foundations and practical strategies.

This book brings together leading experts from around the world to explore the transformative potential of Machine Learning (ML) and the Internet of Things (IoT) in healthcare.

This book provides insights into how AI is changing legal practice, government processes, and individuals' access to those processes, encouraging each of us to consider how technological advances are changing the legal system.

This book provides insights into how AI is changing legal practice, government processes, and individuals' access to those processes, encouraging each of us to consider how technological advances are changing the legal system.

This book provides an ideal guide for Python developers who want to learn how to build applications with large language models.

What are the principles behind intelligent systems?

Gain a deep understanding of applied deep learning on graphs from data, algorithm, and engineering viewpoints to construct enterprise-ready solutions using deep learning on graph data for wide range of domainsKey FeaturesExplore graph data in real-world systems and leverage graph learning for impactful business resultsDive into popular and specialized deep neural architectures like graph convolutional and attention networksLearn how to build scalable and productionizable graph learning solutionsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionWith their combined expertise spanning cutting-edge AI product development at industry giants such as Walmart, Adobe, Samsung, and Arista Networks, Lakshya and Subhajoy provide real-world insights into the transformative world of graph neural networks (GNNs).

Master AI, machine learning, and deep learning with practical insights into RNNs, LSTMs, NLP, and reinforcement learning.

Master AI, machine learning, and deep learning with practical insights into RNNs, LSTMs, NLP, and reinforcement learning.

This book provides a comprehensive overview of the concept of digital twins, emphasising its strategic importance across various commercial domains.

Why has so much of our recent attention been focused on AI while RI (Real Intelligence) is all but forgotten?

This book aims to solve the discrete implementation problems of continuous-time neural network models while improving the performance of neural networks by using various Zhang Time Discretization (ZTD) formulas.

Artificial Intelligence and Ethics is a general and wide-ranging survey of the benefits and ethical dilemmas of artificial intelligence (AI).

Artificial Intelligence (AI) revolves around creating and utilizing intelligent machines through science and engineering.

Work on 10 practical projects, each with a blueprint for a different machine learning technique, and apply them in the real world to fight against cybercrimePurchase of the print or Kindle book includes a free PDF eBookKey FeaturesLearn how to frame a cyber security problem as a machine learning problemExamine your model for robustness against adversarial machine learningBuild your portfolio, enhance your resume, and ace interviews to become a cybersecurity data scientistBook DescriptionMachine learning in security is harder than other domains because of the changing nature and abilities of adversaries, high stakes, and a lack of ground-truth data.