1.065 hasil untuk machine learning
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Data Science Project: An Inductive Learning Approach
"Data Science Project: An Inductive Learning Approach" provides a comprehensive methodology for data science project development, emphasizing software engineering principles essential for reliable solutions. Prof. Dr. Filipe Verri, a senior data science project manager, Scientific Director of…
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Federated Learning: From Theory to Practice
A hands-on introduction to building and understanding federated learning systems, used as the lecture notes for CS-E4740 Federated Learning at Aalto University. Federated learning is presented as distributed optimization over an empirical graph whose nodes carry local datasets and models, covering…
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Deep Learning: Theoretical and Practical Approach
Deep Learning Course Book In Persian This book includes three parts; The first part provides necessary prerequisites for deep learning topics such as linear algebra, statistics and probability, information theory, data mining, signal processing, machine learning, etc. The main issues in deep…
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Deep Learning I: Modelos Sequenciais e Autoencoders
eBook Deep Learning I: Modelos Sequenciais e Autoencoders Oliveira, R. (2020). Deep Learning I: Modelos Sequenciais e Autoencoders . (pp. 1–226). eBook. https://doi.org/10.5281/zenodo.6675400 . Para acesso ao conteúdo clique nos Capítulos, no Título, ou acesse aqui . Apresentação São inúmeras as…
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Mastering Deep Learning: From Tensors to Transformers
Mastering Deep Learning offers a practical, code-first approach to understanding and applying modern AI techniques. The book emphasizes clarity, guiding students, researchers, and practitioners from the fundamentals of deep learning to advanced models for image recognition and text generation, such…
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GAI-MUA: The Grothendieckian Machine
GAI-MUA: The Grothendieckian Machine A Mathematical Universe Architecture for Verifiable and Self-Evolving Artificial Intelligence GAI-MUA: The Grothendieckian Machine is a six-volume program in mathematics, formal reasoning, system architecture, and self-evolving mathematical artificial…
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Deep Learning
Deep Learning is a comprehensive guide that explores the foundational and advanced aspects of deep learning, a subfield of machine learning focused on neural networks with multiple layers. The book begins by introducing core concepts such as artificial neural networks, perceptrons, and the…
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Mathematical Foundations for Reinforcement Learning: A Companion to Reinforcement Learning: Theory and Algorithms
This volume provides the complete but deliberately minimal mathematical foundation needed to study the proofs in Reinforcement Learning: Theory and Algorithms [83]. It consolidates the reusable mathematical objects, assumptions, and proof techniques used in that reference and presents them in…
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Deep Learning & Applications
The book Deep Learning & Applications , authored by Dr. A. Dennis Ananth, Dr. S. Markkandeyan, Dr. M. Rajakumaran, and Dr. B. Lakshmi, explores the foundational principles, advanced architectures, and diverse applications of deep learning in today’s technology-driven landscape. This comprehensive…
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INTERNATIONAL CONFERENCE ON HUMAN MACHINE INTERACTION IN THE DIGITAL ERA (ICHMIDE -2023)
…been active in research and Organizes International Conference on HUMAN MACHINE INTERACTION IN THE DIGITAL ERA (ICHMIDE -2023)- In Association with AIMIST University, Malaysia, and Computer Society of India, Chennai Chapter . It is our privilege to share that this Conference has been supported by…
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Deconstructing Chess: How a 64-Square Game Sharpens the Question of Machine Thinking
This research book uses chess — the oldest and cleanest benchmark in artificial intelligence — to ask one of the hardest questions in the field: does a machine that plays chess at a superhuman level actually think about it, or is it doing something we don't yet have a name for? Over 75 years , the…
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REINFORCEMENT LEARNING: THE FOUNDATIONAL APPROACH
**Author’s Learning** Reinforcement learning (RL) stands as a fundamental paradigm in machine learning, wherein an agent acquires optimal decision-making through sequential interactions with an environment, guided by scalar reward signals to maximize long-term cumulative returns. Unlike supervised…
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Reinforcement Learning: An Introduction
Bibliographic reference / Référence bibliographique (RDA/ISBD) BRITO, João B. G. Reinforcement Learning: An Introduction — Learning Optimal Policies Through Interaction and Reward . 1st ed. – Ghent : Zenodo, 2024. 58 p. ; 29,7 cm. — ( Data Science Series ; vol. 4 ). DOI 10.5281/zenodo.17545935…
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DEEP LEARNING AND NEURAL NETWORKS
…life. At the heart of many recent AI breakthroughs lies the field of Deep Learning and Neural Networks , which enables machines to learn from vast amounts of data and perform tasks that once required human intelligence. From image recognition and speech processing to language translation and…
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Federated and Transfer Learning Applications
The classic example of machine learning is based on isolated learning—a single model for each task using a single dataset. Most deep learning methods require a significant amount of labeled data, preventing their applicability in many areas where there is a shortage. In these cases, the ability of…
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FUNDAMENTALS OF ELECTROMAGNETICS FOR ELECTRICAL MACHINE DESIGN
…that will be included on examinations. In order to facilitate consistent learning and the retention of information, a portion of practice problems has been included to each of the chapters. At the end of each chapter, there is a sufficient number of multiple-choice, short- answer, and test…
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THEORY AND APPLICATIONS IN DEEP LEARNING
With the intention of introducing newbies to these fields, this article covers deep learning in addition to deep learning platforms, methodologies, applications, and open-source datasets. You'll discover the basics of AI and get an overview of deep learning, which will be defined and addressed in…
Juga tersedia di: Zenodo
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DEEP LEARNING FOR BIOMEDICAL DATA ANALYSIS
…the exponential growth in data availability, the role of data science and machine learning in biomedicine has become more crucial than ever. From genomics to electronic health records (EHRs), biomedical research to clinical applications, the promise of data-driven discoveries is transforming how we…
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Learning Machines Building Smarter Models with Data
The exponential growth of data in recent decades has brought forth a new era of intelligent systems and data-driven decision-making. Machine learning often referred to as the art of teaching machines to learn from experience stands at the heart of this transformation. This book, Learning Machines…
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