Hicham Assoudi

Natural Language Processing on Oracle Cloud Infrastructure

Building Transformers-Based Nlp Solutions Using Oracle AI and Hugging Face

• Broschiertes Buch

Produktbeschreibung

This book demonstrates how to use Oracle Cloud Infrastructure (OCI) and Hugging Face technologies to develop advanced NLP solutions. Through a practical case study, it addresses common NLP challenges and offers strategies for creating efficient, cost-effective transformer-based models. By the end of this book, you will have the skills and knowledge to create cutting-edge NLP solutions on OCI, customized to meet the needs of various industries and projects.

The book takes you through the complete NLP solution life cycle-covering data preparation, model fine-tuning, deployment, and monitoring-while highlighting key topics such as cost-effectiveness and responsible AI for NLP implementations. Drawing from real-world experience and offering practical insights, it bridges the gap between theory and practice, equipping you to design and deploy scalable, cost-efficient NLP solutions.

What You Will Learn
Master key NLP concepts and the OCI ecosystemCreate high-quality datasets using Hugging Face and OCI Data Labeling ServiceFine-tune domain-specific pre-trained models from Hugging Face using OCI Data Science Notebook SessionsDeploy and operationalize your models with OCI Data Science Model DeploymentsAutomate the NLP life cycle with OCI Data Science PipelinesImplement cost-effective strategies throughout the entire NLP life cycle, from dataset preparation to model training and deployment

Who This Book Is For

A diverse audience interested in implementing NLP solutions on Oracle Cloud Infrastructure: NLP practitioners, data scientists, and machine learning engineers who want to learn how to leverage Oracle AI and Hugging Face to implement an end-to-end NLP solution life cycle, from data preparation to model deployment; Oracle practitioners who want to expand their Oracle expertise by exploring OCI's advanced capabilities for building and scaling cutting-edge NLP solutions in enterprise environments; business decisionmakers who want to discover the strategic benefits of NLP solutions on OCI, including cost-effectiveness and responsible AI, while driving business value

---

Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Verlag: Apress / Springer, Berlin
• Artikelnr. des Verlages: 979-8-8688-1072-5
• First Edition
• Seitenzahl: 490
• Erscheinungstermin: 14. Dezember 2024
• Englisch
• Abmessung: 254mm x 178mm
• ISBN-13: 9798868810725
• Artikelnr.: 71530772

Autorenporträt

Hicham Assoudi is an accomplished IT professional and AI expert with over 30 years of experience, including more than 25 years specializing in Oracle technologies. He holds a PhD in Computer Science and is also an OCI Certified Architect. Hicham has held key roles such as Technology Manager at Oracle and IT Architect at IBM, offering highly specialized technical consulting to major corporations across Canada, the US, and Europe.   Hicham's journey into AI began over a decade ago during his doctoral studies, where he initially focused on intelligent agents and general machine learning. He later specialized in natural language processing (NLP) from the early days of transformer models, positioning him at the forefront of NLP innovation. As the founder of Typica.ai, an AI startup, Hicham applies cutting-edge research to practical NLP solutions, empowering organizations to leverage NLP for significant business impact.   In addition to his industry contributions, Hicham maintains strong ties to academia as an External Research Associate at the AI Lab of UQAM University in Montreal, bridging the gap between academic research and real-world applications.

Inhaltsangabe

Part 1: Foundations and Case Study Introduction.- Chapter 1: NLP Essentials.- Chapter 2: Oracle Cloud for NLP.- Chapter 3: Healthcare NLP Case Study.- Part2: Case Study Implementation.- Chapter 4: Tenancy Preparation.- Chapter 5: Dataset Preparation.- Chapter 6: Model Fine-tuning.- Part 3: Case Study Deployment and Wrap-Up.- Chapter 7: Model Deployment and Monitoring.- Chapter 8: MLOps and Conclusion.