Denis Rothman graduated from Sorbonne University and Paris-Diderot University, designing one of the very first word2matrix patented embedding and patented AI conversational agents. He began his career authoring one of the first AI cognitive natural language processing (NLP) chatbots applied as an automated language teacher for Moët et Chandon and other companies. He authored an AI resource optimizer for IBM and apparel producers. He then authored an advanced planning and scheduling (APS) solution used worldwide.
Denis Rothman - ebooki
Tytuły autora: Denis Rothman dostępne w księgarni Helion
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Being the first book in the market to dive deep into the Transformers, this book is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers with Python, PyTorch, and TensorFlow
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Transformers for Natural Language Processing. Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 - Second Edition Transformers for Natural Language Processing. Build, train, and fine-tune deep neural network architectures for NLP with Python, Hugging Face, and OpenAI's GPT-3, ChatGPT, and GPT-4 - Second Edition
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Being the first book in the market to dive deep into the Transformers, it is a step-by-step guide for data and AI practitioners to help enhance the performance of language understanding and gain expertise with hands-on implementation of transformers using PyTorch, TensorFlow, Hugging Face, Trax, and AllenNLP.
- PDF + ePub + Mobi pkt
Transformers for Natural Language Processing. Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more Transformers for Natural Language Processing. Build innovative deep neural network architectures for NLP with Python, PyTorch, TensorFlow, BERT, RoBERTa, and more
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In today’s era of AI, accurately interpreting and communicating trustworthy, fair, and secure AI findings have become a crucial skill to master. This book bridges the gap between AI’s pitfalls and potential by helping you build the ability to leverage machine learning with Python to visualize and integrate AI.
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Hands-On Explainable AI (XAI) with Python. Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps Hands-On Explainable AI (XAI) with Python. Interpret, visualize, explain, and integrate reliable AI for fair, secure, and trustworthy AI apps
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Artificial Intelligence (AI) gets your system to think smart and learn intelligently. This book is packed with some of the smartest trending examples with which you will learn the fundamentals of AI. By the end, you will have acquired the basics of AI by practically applying the examples in this book.
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Artificial Intelligence By Example. Acquire advanced AI, machine learning, and deep learning design skills - Second Edition Artificial Intelligence By Example. Acquire advanced AI, machine learning, and deep learning design skills - Second Edition
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Artificial Intelligence(AI), gets your system to think smart and intelligent. This book is packed with some of the smartest and easy-peasy examples through which you will learn the fundamentals of AI. You will have acquired the foundation of AI and understood the practical case studies in this book.
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Artificial Intelligence By Example. Develop machine intelligence from scratch using real artificial intelligence use cases Artificial Intelligence By Example. Develop machine intelligence from scratch using real artificial intelligence use cases
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Explore the transformative potential of RAG-driven LLMs, computer vision, and Generative AI with this comprehensive guide, from basics to building a complex RAG pipeline
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RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone RAG-Driven Generative AI. Build custom retrieval augmented generation pipelines with LlamaIndex, Deep Lake, and Pinecone
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