AI-Modelling and Process

AI-Modelling and Process (Paperback, PRADEEP K. SURI)

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AI-Modelling and Process (Paperback, PRADEEP K. SURI)

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    Highlights
    • Binding: Paperback
    • Publisher: Bluerose Publishers Pvt. Ltd.
    • ISBN: 9789359896021
    • Edition: 2024
    • Pages: 116
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  • Description
    The book delves into the fascinating world of Deep Neural Networks (DNNs), a powerful tool within Artificial Intelligence (AI). It explores how DNNs learn and make predictions based on data. Clarifying DNNs: The book explains the core concepts of DNNs, their structure, and how they extract patterns from training data. Data preparation: Understanding the importance of various datasets, including training, testing, and unseen data, in building robust AI models. Machine Learning and Deep Learning: The book provides a clear overview of Machine Learning (ML) and Deep Learning (DL) as foundational concepts for AI development. Python libraries: Learn about Python libraries commonly used for AI and DNN implementation. Designing AI Management Dashboards: Discover how to create dashboards to visualize and monitor AI performance. Real-world applications of AI: Explore the diverse domains where AI is making a significant impact, including finance, and healthcare. AI Engine integration: Understand the benefits of integrating AI engines with existing systems like ERP. Generative AI: Learn about this exciting subfield of AI focused on creating new data. 50+ video tutorials: The book's website offers video tutorials demonstrating AI forecasting in various domains. Overall, "AI-Modelling and Process" provides a valuable roadmap for understanding and implementing AI in today's data-driven world.
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    Book Details
    Title
    • AI-Modelling and Process
    Publication Year
    • 2024 January
    Product Form
    • Paperback
    Publisher
    • Bluerose Publishers Pvt. Ltd.
    ISBN13
    • 9789359896021
    Book Category
    • Biographies, Memoirs and General Non-Fiction Books
    Book Subcategory
    • Other Books
    Language
    • English
    Contributors
    Author Info
    • The book delves into the fascinating world of Deep Neural Networks (DNNs), a powerful tool within Artificial Intelligence (AI). It explores how DNNs learn and make predictions based on data. Clarifying DNNs: The book explains the core concepts of DNNs, their structure, and how they extract patterns from training data. Data preparation: Understanding the importance of various datasets, including training, testing, and unseen data, in building robust AI models. Machine Learning and Deep Learning: The book provides a clear overview of Machine Learning (ML) and Deep Learning (DL) as foundational concepts for AI development. Python libraries: Learn about Python libraries commonly used for AI and DNN implementation. Designing AI Management Dashboards: Discover how to create dashboards to visualize and monitor AI performance. Real-world applications of AI: Explore the diverse domains where AI is making a significant impact, including finance, and healthcare. AI Engine integration: Understand the benefits of integrating AI engines with existing systems like ERP. Generative AI: Learn about this exciting subfield of AI focused on creating new data. 50+ video tutorials: The book's website offers video tutorials demonstrating AI forecasting in various domains. Overall, "AI-Modelling and Process" provides a valuable roadmap for understanding and implementing AI in today's data-driven world.
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