Neural networks and fuzzy systems

This book offers a compelling look into the future of artificial intelligence, where AI systems are no longer limited to just processing information, but can perceive the world through synthetic senses.

Mathematics is the foundation of machine learning algorithms.

This book studies different classification, detection, and decision fusion algorithms, and it helps practitioners deal with uncertainty in their data sets.

Mathematics is the foundation of machine learning algorithms.

This book offers a compelling look into the future of artificial intelligence, where AI systems are no longer limited to just processing information, but can perceive the world through synthetic senses.

This book studies different classification, detection, and decision fusion algorithms, and it helps practitioners deal with uncertainty in their data sets.

For the first time in history, the most powerful artificial intelligence (AI) works through language itself: The same medium humans use to think and communicate.

For the first time in history, the most powerful artificial intelligence (AI) works through language itself: The same medium humans use to think and communicate.

Topics in Modal Analysis, Testing & Parameter Identification I, Volume 9: Proceedings of the 43rd IMAC, A Conference and Exposition on Structural Dynamics, 2025, the ninth volume of twelve from the Conference brings together contributions to this important area of research and engineering.

The current era of artificial intelligence and machine learning (AIML) tools has transformed the workings of vast swaths of our private, working, and social lives beyond recognition.

The current era of artificial intelligence and machine learning (AIML) tools has transformed the workings of vast swaths of our private, working, and social lives beyond recognition.

Gain hands-on experience building, fine-tuning, and deploying GenAI applications using DeepSeekKey FeaturesExplore DeepSeek's architecture, training data, and reasoning capabilitiesBuild agents, fine-tune with distillation, and deploy with CI/CD pipelinesApply DeepSeek to real-world use cases like coding, ideation, and legal analysisPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionLearn how to build, fine-tune, and deploy AI systems using DeepSeek, one of the most influential open-source large language models available today.

Gain hands-on experience building, fine-tuning, and deploying GenAI applications using DeepSeekKey FeaturesExplore DeepSeek's architecture, training data, and reasoning capabilitiesBuild agents, fine-tune with distillation, and deploy with CI/CD pipelinesApply DeepSeek to real-world use cases like coding, ideation, and legal analysisPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionLearn how to build, fine-tune, and deploy AI systems using DeepSeek, one of the most influential open-source large language models available today.

This dissertation considers various questions with respect to the effects of salinity on nutrification: what are the main inhibiting factors causing the effects, do all salts have similar effects, what is the maximum acceptable salt level, are ammonia oxidisers or nitrite oxidizers most sensitive to salt stress, can nitrifiers adapt to long term salt stress and are some specific nitrifiers more resistant to salt stress than others?

This dissertation considers various questions with respect to the effects of salinity on nutrification: what are the main inhibiting factors causing the effects, do all salts have similar effects, what is the maximum acceptable salt level, are ammonia oxidisers or nitrite oxidizers most sensitive to salt stress, can nitrifiers adapt to long term salt stress and are some specific nitrifiers more resistant to salt stress than others?

Learning-Driven Game Theory for AI: Concepts, Models, and Applications offers in-depth coverage of recent methodological and conceptual advancements in various disciplines of Dynamic Games, namely differential and discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in a variety of fields, such as computer science, biology, economics, and management science.

Topics in Modal Analysis, Testing & Parameter Identification I, Volume 9: Proceedings of the 43rd IMAC, A Conference and Exposition on Structural Dynamics, 2025, the ninth volume of twelve from the Conference brings together contributions to this important area of research and engineering.

The First International Conference on Computer Vision, Communication Systems, and Computational Intelligence (CVCNCE 2025), organised by the Department of Electronics and Communication Engineering at Francis Xavier Engineering College, Tirunelveli, was held on 08-09 May 2025 in hybrid mode.

The First International Conference on Computer Vision, Communication Systems, and Computational Intelligence (CVCNCE 2025), organised by the Department of Electronics and Communication Engineering at Francis Xavier Engineering College, Tirunelveli, was held on 08-09 May 2025 in hybrid mode.

A hands-on guide to powerful graph-based deep learning models.

Distant galaxies, dark matter, black holes elusive, incomprehensible and inhospitable these are the building blocks of modern physics.

Master the art of building AI agents with this hands-on guide to orchestration, multi-agent systems, real-world case studies, and ethical insights to drive immediate business impactKey FeaturesBuild production-ready AI agents with hands-on tutorials for diverse industry applicationsExplore multi-agent system architectures with practical frameworks for orchestrator comparisonFuture-proof your AI development with ethical implementation strategies and security patternsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAs AI agents evolve to take on complex tasks and operate autonomously, you need to learn how to build these next-generation systems.

Deep learning systems have gotten really great at identifying patterns in text, images, and video.

AI as a Service is a practical handbook to building and implementing serverless AI applications, without bogging you down with a lot of theory.

How does the computer learn to understand what it sees?

Probabilistic Deep Learning is a hands-on guide to the principles that support neural networks.

Discover valuable machine learning techniques you can understand and apply using just high-school math.

Summary Machine learning (ML) is a collection of programming techniques for discovering relationships in data.

Summary You are going to need more than technical knowledge to succeed as a data scientist.

SummaryGrokking Deep Learning teaches you to build deep learning neural networks from scratch!

Grokking Deep Reinforcement Learning uses engaging exercises to teach you how to build deep learning systems.

Sharpen your coding skills by exploring established computer science problems!

Summary Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists.

SummaryDeep Learning for Search teaches you how to improve the effectiveness of your search by implementing neural network-based techniques.

From start to finish, the best book to help you learn AI algorithms and recall why and how you use them.

There's a great deal of wisdom in a crowd, but how do you listen to a thousand people talking at once?

Deliver huge improvements to your machine learning pipelines without spending hours fine-tuning parameters!

SummaryDeep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface.

Summary Deep learning has transformed the fields of computer vision, image processing, and natural language applications.

Summary Imagine predicting which customers are thinking about switching to a competitor or flagging potential process failures before they happen Think about the benefits of forecasting tedious business processes and back-office tasks Envision quickly gauging customer sentiment from social media content (even large volumes of it).

SummaryDeep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI.

Deep learning from the ground up using R and the powerful Keras library!

Master the art of building AI agents with this hands-on guide to orchestration, multi-agent systems, real-world case studies, and ethical insights to drive immediate business impactKey FeaturesBuild production-ready AI agents with hands-on tutorials for diverse industry applicationsExplore multi-agent system architectures with practical frameworks for orchestrator comparisonFuture-proof your AI development with ethical implementation strategies and security patternsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionAs AI agents evolve to take on complex tasks and operate autonomously, you need to learn how to build these next-generation systems.

This book presents a comprehensive exploration of structural pattern recognition with a clear understanding of graph representation and manipulation.

Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric and DGLFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesMaster new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)Explore GML frameworks and their main characteristicsLeverage LLMs for machine learning on graphs and learn about temporal learningPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGraph Machine Learning, Second Edition builds on its predecessor s success, delivering the latest tools and techniques for this rapidly evolving field.

Enhance your data science skills with this updated edition featuring new chapters on LLMs, temporal graphs, and updated examples with modern frameworks, including PyTorch Geometric and DGLFree with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesMaster new graph ML techniques through updated examples using PyTorch Geometric and Deep Graph Library (DGL)Explore GML frameworks and their main characteristicsLeverage LLMs for machine learning on graphs and learn about temporal learningPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionGraph Machine Learning, Second Edition builds on its predecessor s success, delivering the latest tools and techniques for this rapidly evolving field.

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

Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs)Key FeaturesImplement real-world applications of LLMs and generative AIFine-tune models with PEFT and LoRA to speed up trainingExpand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndexPurchase of the print or Kindle book includes a free eBook in PDF formatBook DescriptionBecome an expert in Generative AI through immersive, hands-on projects that leverage today's most powerful models for Natural Language Processing (NLP) and computer vision.