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README.md
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<div class="grid lg:grid-cols-3 gap-x-4 gap-y-7">
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<p class="lg:col-span-3">
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<strong>Más de 30 años aplicando Big Data e Inteligencia Artificial</strong>
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Te ofrecemos soluciones Big Data y técnicas de IA adaptadas a las necesidades de tu negocio para conseguir una ventaja competitiva que produzca beneficios tangibles.
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</p>
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<a
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href="https://huggingface.co/blog/the-partnership-amazon-sagemaker-and-hugging-face"
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class="block overflow-hidden group"
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>
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<div
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class="w-full h-40 object-cover mb-2 bg-indigo-100 rounded-lg flex items-center justify-center dark:bg-gray-900 dark:group-hover:bg-gray-850"
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>
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<img
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alt=""
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src="https://www.iic.uam.es/wp-content/uploads/2022/03/algoritmos-bioinspirados-1.jpg"
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class="w-40"
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/>
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</div>
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<div class="underline">Algoritmos bioinspirados: optimización basada en la evolución natural</div>
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</a>
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<a href="https://youtu.be/ok3hetb42gU" class="block overflow-hidden">
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<img
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alt=""
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src="https://www.iic.uam.es/wp-content/uploads/2022/03/ingeniero-de-datos.jpg"
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class="w-full h-40 object-cover mb-2 bg-gray-300 rounded-lg"
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/>
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<div class="underline">Científico, ingeniero y arquitecto de datos, ¿quién es quién en Inteligencia Artificial?</div>
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</a>
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<a
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href="https://huggingface.co/docs/sagemaker"
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class="block overflow-hidden group"
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>
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<div
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class="w-full h-40 object-cover mb-2 bg-gray-900 group-hover:bg-gray-850 rounded-lg flex items-start justify-start"
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>
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<img
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alt=""
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src="https://www.iic.uam.es/wp-content/uploads/2022/03/optimizacion-quantum.jpg"
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class="w-44 p-4"
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/>
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</div>
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<div class="underline">Optimización con computadores cuánticos</div>
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</a>
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<div class="lg:col-span-3">
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<p class="mb-2">
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To train Hugging Face models in Amazon SageMaker, you can use the
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Hugging Face Deep Learning Contrainers (DLCs) and the Hugging Face
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support in the SageMaker Python SDK.
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</p>
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<p class="mb-2">
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The DLCs are fully integrated with the SageMaker distributed training
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libraries to train models more quickly using the latest generation of
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accelerated computing instances available on Amazon EC2. With the
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SageMaker Python SDK, you can start training with just a single line of
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code, enabling your teams to move from idea to production more quickly.
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</p>
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<p class="mb-2">
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To deploy Hugging Face models in Amazon SageMaker, you can use the
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Hugging Face Deep Learning Containers with the new Hugging Face
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Inference Toolkit.
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</p>
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<p class="mb-2">
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With the new Hugging Face Inference DLCs, deploy your trained models for
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inference with just one more line of code, or select any of the 10,000+
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models publicly available on the 🤗 Hub, and deploy them with Amazon
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SageMaker, to easily create production-ready endpoints that scale
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seamlessly, with built-in monitoring and enterprise-level security.
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</p>
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<p>
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More information: <a
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href="https://aws.amazon.com/blogs/machine-learning/aws-and-hugging-face-collaborate-to-simplify-and-accelerate-adoption-of-natural-language-processing-models/"
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class="underline">AWS blog post</a
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>,
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<a
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href="https://discuss.huggingface.co/c/sagemaker/17"
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class="underline">Community Forum</a
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>
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</p>
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</div>
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</div>
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