Course Curriculum

16 Chapters · 16 Lessons

  1. 1

    Book Preview

    1. Book Preview Free preview
  2. 2

    Introduction

    1. (Included in full purchase)

      Introduction

  3. 3

    Chapter 1 : Introduction to Llama Series

    1. (Included in full purchase)

      Introduction to Llama Series

  4. 4

    Chapter 2 : The Architecture of Llama Models

    1. (Included in full purchase)

      The Architecture of Llama Models

  5. 5

    Chapter 3 : Evolution of Llama

    1. (Included in full purchase)

      Evolution of Llama

  6. 6

    Chapter 4 : Implementing NLP Tasks with Llama

    1. (Included in full purchase)

      Implementing NLP Tasks with Llama

  7. 7

    Chapter 5 : Fine-Tuning Llama for NLP

    1. (Included in full purchase)

      Fine-Tuning Llama for NLP

  8. 8

    Chapter 6 : Real-World Use Cases of Llama

    1. (Included in full purchase)

      Real-World Use Cases of Llama

  9. 9

    Chapter 7 : Performance Tuning for Llama Models

    1. (Included in full purchase)

      Performance Tuning for Llama Models

  10. 10

    Chapter 8 : Deploying Llama Models at Scale

    1. (Included in full purchase)

      Deploying Llama Models at Scale

  11. 11

    Chapter 9 : Troubleshooting and Improving Llama Models

    1. (Included in full purchase)

      Troubleshooting and Improving Llama Models

  12. 12

    Chapter 10 : Transfer Learning Techniques with Llama

    1. (Included in full purchase)

      Transfer Learning Techniques with Llama

  13. 13

    Chapter 11 : Ethical Considerations in NLP with Llama

    1. (Included in full purchase)

      Ethical Considerations in NLP with Llama

  14. 14

    Chapter 12 : Practical Applications of Llama4

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      Practical Applications of Llama4

  15. 15

    Chapter 13 : Future Directions and Advancements in Llama

    1. (Included in full purchase)

      Future Directions and Advancements in Llama

  16. 16

    Index

    1. (Included in full purchase)

      Index

About the Course

Llama models have rapidly emerged as a cornerstone in natural language processing, redefining how AI systems understand and generate human language. From their efficient architecture to the cutting-edge advancements in Llama 4, these models enable enterprises, researchers, and developers to build powerful, scalable, and responsible NLP solutions. This book, Ultimate Llama for Natural Language Processing (NLP), takes you on a structured journey through the evolution and applications of Llama. It begins with the foundations of the Llama series and its architecture, before progressing to core NLP tasks such as classification, summarization, sentiment analysis, and conversational AI. Subsequent chapters cover fine-tuning, transfer learning, optimization, and deployment at enterprise scale, with practical insights into real-world industry use cases. The book also addresses troubleshooting, ethical AI, and the future of multimodal and sparse Mixture-of-Experts models. Thus, by the end, readers will be well-equipped to train, adapt, and deploy Llama models across domains such as healthcare, finance, and customer engagement. 

About the Author

Gaurav Singh is a visionary leader and accomplished professional in Data Science, Machine Learning, and AI Cloud Technologies, with a strong track record of delivering enterprise-scale AI solutions that drive transformative business impact. With deep expertise in LightGBM, TensorFlow, Deep Learning, Large Language Models (LLMs), Generative AI, Agentic AI, NLP, Prompt Engineering, and Responsible AI, he bridges cutting-edge research with practical enterprise applications. Renowned for his Python-driven AI development, he builds intelligent systems leveraging Azure Gen AI, Databricks,Vertex AI, GCP, Synapse, and Snowflake to enable automation, accelerate decision-making, and deliver actionable insights.