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5761
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5762
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5763
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5764Publicado 2019Materias:Grabación no musical
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5765
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5766Publicado 2022Materias: “…Artificial intelligence Industrial applications…”
Libro electrónico -
5767Publicado 2024Materias:Libro electrónico
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5768Publicado 2024Materias:Libro electrónico
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5769
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5770Publicado 2024Materias: “…Artificial intelligence…”
Video -
5771
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5772
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5773Publicado 2023Materias:Libro electrónico
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5774
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5775
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5776Publicado 2024Materias: “…Artificial intelligence…”
Vídeo online -
5777
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5778Publicado 2024Tabla de Contenidos: “…Intro -- Title Page -- Copyright and Credits -- Dedications -- Foreword -- Contributors -- Table of Contents -- Preface -- Part 1: Foundations of Generative AI and the Evolution of Large Language Models -- Chapter 1: Understanding Generative AI: An Introduction -- Generative AI -- Distinguishing generative AI from other AI models -- Briefly surveying generative approaches -- Clarifying misconceptions between discriminative and generative paradigms -- Choosing the right paradigm -- Looking back at the evolution of generative AI -- Overview of traditional methods in NLP -- Arrival and evolution of transformer-based models -- Development and impact of GPT-4 -- Looking ahead at risks and implications -- Introducing use cases of generative AI -- The future of generative AI applications -- Summary -- References -- Chapter 2: Surveying GenAI Types and Modes: An Overview of GANs, Diffusers, and Transformers -- Understanding General Artificial Intelligence (GAI) Types - distinguishing features of GANs, diffusers, and transformers -- Deconstructing GAI methods - exploring GANs, diffusers, and transformers -- A closer look at GANs -- A closer look at diffusion models -- A closer look at generative transformers -- Applying GAI models - image generation using GANs, diffusers, and transformers -- Working with Jupyter Notebook and Google Colab -- Stable diffusion transformer -- Scoring with the CLIP model -- Summary -- References -- Chapter 3: Tracing the Foundations of Natural Language Processing and the Impact of the Transformer -- Early approaches in NLP -- Advent of neural language models -- Distributed representations -- Transfer Learning -- Advent of NNs in NLP -- The emergence of the Transformer in advanced language models -- Components of the transformer architecture -- Sequence-to-sequence learning…”
Libro electrónico -
5779
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5780Publicado 2024Materias:Libro electrónico
