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  <titleInfo>
    <title>Mastering LLM Applications with LangChain and Hugging Face: Practical Insights into LLM Deployment and Use Cases</title>
  </titleInfo>
  <name type="personal">
    <namePart>Pathan, Hunidkhan</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <name type="personal">
    <namePart>Nayankumar Gajjar</namePart>
    <role>
      <roleTerm authority="marcrelator" type="text">creator</roleTerm>
    </role>
  </name>
  <typeOfResource>text</typeOfResource>
  <originInfo>
    <place>
      <placeTerm type="text">New Delhi</placeTerm>
    </place>
    <publisher>BPB Publications</publisher>
    <dateIssued>2026</dateIssued>
    <issuance>monographic</issuance>
  </originInfo>
  <language>
    <languageTerm authority="iso639-2b" type="code">eng</languageTerm>
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  <tableOfContents>1. Introduction to Python and Code Editors
2. Installation of Python, Required Packages, and Code Editors
3. Ways to Run Python Scripts
4. Introduction to NLP and its Concepts
5. Introduction to Large Language Models
6. Introduction of LangChain, Usage and Importance
7. Introduction of Hugging Face, its Usage and Importance
8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub
9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models
10. Integrating LLMs into Real-World Applications–Case Studies
11. Deploying LLMs in Cloud Environments for Scalability
12. Future Directions: Advances in LLMs and Beyond
Appendix A: Useful Tips for Efficient LLM Experimentation
Appendix B: Resources and References</tableOfContents>
  <note type="statement of responsibility">by Hunaidkhan Pathan and Nayankumar Gajjar</note>
  <subject>
    <topic>Computer science</topic>
  </subject>
  <subject>
    <topic>Special computer methods (AI, barcoding, VR, web design, social media) </topic>
  </subject>
  <subject>
    <topic>Artificial Intelligence </topic>
  </subject>
  <subject>
    <topic>AI</topic>
  </subject>
  <subject>
    <topic>Natural Language Processing</topic>
  </subject>
  <classification authority="ddc">006.35 PAT-M</classification>
  <identifier type="isbn">9789365891041</identifier>
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