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Applied Text Analytics for the Enterprise: Implementing Deep Learning and Natural Language Processing with LLM
Paperback
Series: The Enterprise Data Science Mastery, Book 3
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Publisher: Independently Published
Pages: 206
Weight: 0.81
Height: 0.44 Width: 7.00 Depth: 10.00
Language: English
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
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