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Applied Text Analytics for the Enterprise: Implementing Deep Learning and Natural Language Processing with LLM: 3 - Brossura
Libro 3 di 4: The Enterprise Data Science Mastery Series
Sinossi
Your organization is sitting on a massive source of intelligence buried in text.
Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information.
Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).
Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.
Inside, you'll learn how to:
- Build scalable NLP and text analytics workflows for enterprise data
- Apply deep learning architectures, attention mechanisms, and transformers to text
- Develop named entity recognition and information extraction systems
- Perform sentiment analysis and topic modeling across large text collections
- Build semantic search systems using document embeddings and vector databases
- Design Retrieval-Augmented Generation (RAG) systems grounded in organizational data
- Understand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniques
- Adapt NLP and LLM solutions for specialized domains and business workflows
- Integrate AI models through enterprise APIs and automated processes
- Evaluate accuracy, faithfulness, feedback loops, and business impact
Build smarter text analytics systems and unlock more value from the information your organization already has.
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Applied Text Analytics for the Enterprise (Paperback)
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Paperback. Condizione: new. Paperback. Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: Build scalable NLP and text analytics workflows for enterprise dataApply deep learning architectures, attention mechanisms, and transformers to textDevelop named entity recognition and information extraction systemsPerform sentiment analysis and topic modeling across large text collectionsBuild semantic search systems using document embeddings and vector databasesDesign Retrieval-Augmented Generation (RAG) systems grounded in organizational dataUnderstand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniquesAdapt NLP and LLM solutions for specialized domains and business workflowsIntegrate AI models through enterprise APIs and automated processesEvaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9798170563791
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Applied Text Analytics for the Enterprise: Implementing Deep Learning and Natural Language Processing with LLM (The Enterprise Data Science Mastery Series)
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Applied Text Analytics for the Enterprise (Paperback)
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Paperback. Condizione: new. Paperback. Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: Build scalable NLP and text analytics workflows for enterprise dataApply deep learning architectures, attention mechanisms, and transformers to textDevelop named entity recognition and information extraction systemsPerform sentiment analysis and topic modeling across large text collectionsBuild semantic search systems using document embeddings and vector databasesDesign Retrieval-Augmented Generation (RAG) systems grounded in organizational dataUnderstand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniquesAdapt NLP and LLM solutions for specialized domains and business workflowsIntegrate AI models through enterprise APIs and automated processesEvaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798170563791
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Applied Text Analytics for the Enterprise : Implementing Deep Learning and Natural Language Processing with LLM
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Taschenbuch. Condizione: Neu. Neuware - Your organization is sitting on a massive source of intelligence buried in text. Contracts, customer feedback, reports, documents, support conversations, and other unstructured data contain valuable information. Applied Text Analytics for the Enterprise shows you how to turn that information into practical business intelligence using modern NLP, deep learning, and Large Language Models (LLMs).Designed for professionals working with enterprise data and AI, this practical guide takes you from modern text-processing fundamentals to sophisticated production applications.Inside, you'll learn how to: - Build scalable NLP and text analytics workflows for enterprise data- Apply deep learning architectures, attention mechanisms, and transformers to text- Develop named entity recognition and information extraction systems- Perform sentiment analysis and topic modeling across large text collections- Build semantic search systems using document embeddings and vector databases- Design Retrieval-Augmented Generation (RAG) systems grounded in organizational data- Understand when to prompt, fine-tune, or use parameter-efficient fine-tuning techniques- Adapt NLP and LLM solutions for specialized domains and business workflows- Integrate AI models through enterprise APIs and automated processes- Evaluate accuracy, faithfulness, feedback loops, and business impactFrom unstructured data to actionable intelligence, this book connects advanced AI techniques with the practical realities of enterprise implementation. Build smarter text analytics systems and unlock more value from the information your organization already has. Codice articolo 9798170563791
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