📱 eBook en inglés ULTIMATE LLAMA FOR NATURAL LANGUAGE PROCESSING (NLP): BUILD, FINE-TUNE, AND SCALE NEXT-GENERATION NLP SOLUTIONS WITH LLAMA TO POWER FUTURE-READY AI SYSTEMS

Build, Scale and Optimize Cutting-Edge NLP with Llama for Next Gen AI.
Key Features ● Explore Llama’s evolution and innovations for next-gen NLP. ● Implement real-world NLP tasks with step-by-step examples. ● Fine-tune, optimize, and deploy Llama at enterprise scale.
Book Description 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.
What you will learn ● Understand Llama’s evolution, architecture, and unique innovations in NLP. ● Implement core NLP tasks like classification, NER, and summarization. ● Fine-tune Llama for custom domains using advanced transfer learning. ● Optimize inference speed, and deploy Llama models at enterprise scale. ● Troubleshoot, monitor, and continuously improve Llama model performance. ● Apply Llama 4 to real-world industry use cases and multimodal AI.