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    Artificial intelligent algorithms, motivation, and terminology
    (Elsevier, 2024) Pour Haji Kazem, Ali Asghar
    In the era of rapid technological advancements, few fields have garnered as much attention and excitement as artificial intelligence. The fusion of human-like intelligence with machines has not only transformed industries but also reshaped the very fabric of our lives. This article takes you on a captivating journey through the realms of artificial intelligent algorithms, delves into the motivational aspects driving this innovation, and familiarizes you with the essential terminology that underpins this fascinating domain. © 2024 Elsevier Inc. All rights reserved.
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    Learning theory
    (Elsevier, 2024) Pour Haji Kazem, Ali Asghar
    This chapter addresses fundamental aspects of learning theory, its ethical implications in model development and deployment, its integration with decision-making processes, and future directions. The introduction highlights learning theory's role in bridging data and informed choices, while ethical considerations underscore the need to address bias, transparency, and societal impact. The interplay between learning theory and decision-making is explored, enabling systems to navigate uncertainty. Looking ahead, the evolution of learning theory is expected to encompass explainable AI, neuroscience influences, ethical considerations, and integration with emerging technologies, promising transformative advancements across various domains. © 2024 Elsevier Inc. All rights reserved.
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    Neural networks
    (Elsevier, 2024) Pour Haji Kazem, Ali Asghar
    This chapter provides a comprehensive overview of neural networks as a powerful machine learning technique. It explores the fundamental concepts behind neural networks, shedding light on their structure and functioning. Beyond their technical aspects, the chapter delves into the significant role neural networks play in the realm of decision-making. By understanding how neural networks process and analyze data to make informed predictions and decisions, readers will gain valuable insights into the applications and implications of this technology in various domains. © 2024 Elsevier Inc. All rights reserved.