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Hugging Face Transformers Essentials


Hugging Face Transformers Essentials
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Hugging Face Transformers Essentials


Hugging Face Transformers Essentials
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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-05

Hugging Face Transformers Essentials written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-05 with Computers categories.


"Hugging Face Transformers Essentials: From Fine-Tuning to Deployment" is an authoritative guide designed for those seeking to harness the power of state-of-the-art transformer models in natural language processing. Bridging the gap between foundational theory and practical application, this book equips readers with the knowledge to leverage Hugging Face's transformative ecosystem, enabling them to implement and optimize these powerful models effectively. Whether you are a beginner taking your first steps into the realm of AI or an experienced practitioner looking to deepen your expertise, this book offers a structured approach to mastering cutting-edge techniques in NLP. Spanning a comprehensive array of topics, the book delves into the mechanics of building, fine-tuning, and deploying transformer models for diverse applications. Readers will explore the intricacies of transfer learning, domain adaptation, and custom training while understanding the vital ethical considerations and implications of responsible AI development. With its meticulous attention to detail and insights into future trends and innovations, this text serves as both a practical manual and a thought-provoking resource for navigating the evolving landscape of AI and machine learning technologies.



Hugging Face Transformers Essentials


Hugging Face Transformers Essentials
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Author : Robert Johnson
language : en
Publisher:
Release Date : 2025

Hugging Face Transformers Essentials written by Robert Johnson and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Computers categories.




Generative Ai Essentials


Generative Ai Essentials
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Author : Dr. Priyanka Singh
language : en
Publisher: BPB Publications
Release Date : 2025-01-07

Generative Ai Essentials written by Dr. Priyanka Singh and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-07 with Computers categories.


DESCRIPTION Generative AI is changing the way we think about creativity and problem-solving. This book is your go-to guide for understanding and working with this exciting technology. This book offers a clear introduction to generative AI, starting with basics like machine learning and deep learning. It explains key models, including GANs and VAEs, breaking down their architectures and training methods. You will discover how Transformer models like GPT have transformed natural language processing and enabled advancements in language generation. The book explores practical applications such as image synthesis, style transfer, and text generation, showing how generative AI merges technology with creativity. Advanced topics like reinforcement learning, AI ethics, and bias are also covered. Practical tips for creating your own generative AI models, along with insights into the future of this groundbreaking field, making it an essential resource for AI enthusiasts and professionals. By the end of this book, you will have a firm grasp of generative AI concepts and practical skills to get you started. You will be well-prepared to use cloud platforms like AWS, Azure, and GCP to build and launch powerful generative AI projects. From creating realistic images to crafting natural text, you will explore hands-on examples while tackling important ethical questions. This book gives you the skills and confidence to explore the limitless potential of generative AI. KEY FEATURES ● Learn GANs, VAEs, and Transformers with real-world applications. ● Build scalable generative AI models using AWS, Azure, and GCP. ● Explore ethical AI, creative projects, and future trends in technology. WHAT YOU WILL LEARN ● Build foundational knowledge of generative AI principles and models. ● Apply machine learning and deep learning for creative content generation. ● Leverage GANs, VAEs, and Transformer models in real-world scenarios. ● Master cloud tools for scalable generative AI development. ● Address ethical challenges and implement responsible AI practices. ● Explore advanced applications and future directions of generative AI WHO THIS BOOK IS FOR This book is designed for data scientists, machine learning engineers, software developers, cloud professionals, educators, students, and creative professionals. TABLE OF CONTENTS 1. Introduction to Generative AI 2. Generative Adversarial Networks 3. Variational Autoencoders 4. Transformer Models and Language Generation 5. Image Generation and Style Transfer 6. Text Generation and Language Models with Real-time Examples 7. Generative AI in Art and Creativity 8. Exploring Advanced Concepts 9. Future Direction and Challenges 10. Building Your Own-Generative AI Models 11. Conclusion and Outlook Appendices



Essential Solutions Architect S Handbook


Essential Solutions Architect S Handbook
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Author : Bikramjit Debnath
language : en
Publisher: BPB Publications
Release Date : 2025-04-30

Essential Solutions Architect S Handbook written by Bikramjit Debnath and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-30 with Computers categories.


DESCRIPTION In an era where cloud computing, AI, and automation are reshaping industries, this book offers a comprehensive guide for IT professionals seeking to master modern software architecture. It will help bridge the gap between technical expertise and strategic leadership, empowering developers and mid-career professionals to stay ahead in an AI-driven, cloud-first world. Structured into six categories, this book covers key areas such as cloud foundations and migration, modern application development, and AI and advanced technologies. Readers will learn strategies for seamless cloud migration, microservices, serverless computing, and real-time data processing. This book will also provide insights into AI architecture, MLOps, and cloud data warehousing. The book’s focus on infrastructure automation, observability, and FinOps ensures operational efficiency while preparing you for future technological trends like hybrid/multi-cloud strategies, quantum computing, and sustainable IT practices. After reading this book, readers will have gained practical skills in cloud architecture, AI deployment, and data-driven decision-making. With strategic insights and industry best practices, they will be well-equipped to take on leadership roles such as solution architect, enterprise architect, or CTO, driving innovation and shaping the future of technology in their organizations. WHAT YOU WILL LEARN ● Understand solution architecture principles and design scalable solutions. ● Learn cloud migration strategies, including data center and application assessments. ● Explore modern application design practices like microservices and serverless. ● Master data management, governance, and real-time data processing techniques. ● Gain insights into generative AI, AI operationalization, and MLOps. ● Automate infrastructure with IaC, observability, and site reliability engineering. WHO THIS BOOK IS FOR This book is designed for experienced cloud engineers, cloud developers, systems administrators, and solutions architects who aim to expand their expertise toward a CTO-level understanding. It is perfect for professionals with intermediate to advanced knowledge of cloud technologies, systems architecture, and programming, seeking to elevate their strategic and technical skills. TABLE OF CONTENTS 1. Introduction to Solution Architecture 2. Cloud Migration Essentials 3. Operational Excellence in Cloud 4. Modern Application Architecture 5. Development Practices and Tools 6. Data Architecture and Processing 7. Data Strategy and Governance 8. Advanced Analytics 9. Generative AI and Machine Learning 10. Automation and Infra Management 11. FinOps Foundations 12. Security, Privacy, and Ethics 13. Innovation and Future Technologies 14. CTO’s Playbook for Transformation APPENDIX: Additional Resources for Further Learning



Langchain Essentials


Langchain Essentials
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Author : Robert Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-01-06

Langchain Essentials written by Robert Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-06 with Computers categories.


"LangChain Essentials: From Basics to Advanced AI Applications" serves as a comprehensive guide to mastering LangChain, a modern programming paradigm crafted to meet the dynamic challenges of contemporary software development. This book meticulously explores LangChain's architecture, providing readers with a foundational understanding of its core components, effective programming practices, and optimization techniques. Through a structured approach, it transitions from fundamental concepts to complex implementations, enabling learners to build robust and efficient applications across various domains. The book delves into LangChain's versatile use in areas such as artificial intelligence, web and mobile development, and data analytics, illustrating its capability to seamlessly integrate with cutting-edge technologies. With an emphasis on practical applications, it offers real-world case studies and detailed examples, ensuring readers can apply LangChain concepts effectively to real projects. Whether you are a beginner looking to understand the basics or a seasoned developer aiming to leverage LangChain's advanced features, this book provides the insights and skills needed to innovate and excel in the ever-evolving tech landscape.



Learn Openai Whisper


Learn Openai Whisper
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Author : Josué R. Batista
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-31

Learn Openai Whisper written by Josué R. Batista and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.


Master automatic speech recognition (ASR) with groundbreaking generative AI for unrivaled accuracy and versatility in audio processing Key Features Uncover the intricate architecture and mechanics behind Whisper's robust speech recognition Apply Whisper's technology in innovative projects, from audio transcription to voice synthesis Navigate the practical use of Whisper in real-world scenarios for achieving dynamic tech solutions Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAs the field of generative AI evolves, so does the demand for intelligent systems that can understand human speech. Navigating the complexities of automatic speech recognition (ASR) technology is a significant challenge for many professionals. This book offers a comprehensive solution that guides you through OpenAI's advanced ASR system. You’ll begin your journey with Whisper's foundational concepts, gradually progressing to its sophisticated functionalities. Next, you’ll explore the transformer model, understand its multilingual capabilities, and grasp training techniques using weak supervision. The book helps you customize Whisper for different contexts and optimize its performance for specific needs. You’ll also focus on the vast potential of Whisper in real-world scenarios, including its transcription services, voice-based search, and the ability to enhance customer engagement. Advanced chapters delve into voice synthesis and diarization while addressing ethical considerations. By the end of this book, you'll have an understanding of ASR technology and have the skills to implement Whisper. Moreover, Python coding examples will equip you to apply ASR technologies in your projects as well as prepare you to tackle challenges and seize opportunities in the rapidly evolving world of voice recognition and processing.What you will learn Integrate Whisper into voice assistants and chatbots Use Whisper for efficient, accurate transcription services Understand Whisper's transformer model structure and nuances Fine-tune Whisper for specific language requirements globally Implement Whisper in real-time translation scenarios Explore voice synthesis capabilities using Whisper's robust tech Execute voice diarization with Whisper and NVIDIA's NeMo Navigate ethical considerations in advanced voice technology Who this book is for Learn OpenAI Whisper is designed for a diverse audience, including AI engineers, tech professionals, and students. It's ideal for those with a basic understanding of machine learning and Python programming, and an interest in voice technology, from developers integrating ASR in applications to researchers exploring the cutting-edge possibilities in artificial intelligence.



Python Gpt Cookbook


Python Gpt Cookbook
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Author : Dr. Neil Williams
language : en
Publisher: BPB Publications
Release Date : 2025-03-19

Python Gpt Cookbook written by Dr. Neil Williams and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-19 with Computers categories.


DESCRIPTION GPT has redefined the landscape of AI, enabling the creation of powerful language models capable of diverse applications. The objective of the Python GPT Cookbook is to equip readers with practical recipes and foundational knowledge to build business solutions using GPT and Python. The book is divided into four parts. The first covers the basics, the second teaches the fundamentals of NLP, the third delves into applying GPT in various fields, and the fourth provides a conclusion. Each chapter includes recipes and practical insights to help readers deepen their understanding and apply the concepts presented. This cookbook approach delivers 78 practical recipes, including creating OpenAI accounts, utilizing playgrounds and API keys. You will learn text preprocessing, embeddings, fine-tuning, and GPT integration with Hugging Face. Learn to implement GPT using PyTorch and TensorFlow, convert models, and build authenticated actions. Applications include chatbots, email summarization, DBA copilots, and use cases in marketing, sales, IP, and manufacturing. By the end of the book, readers will have a robust understanding of GPT models and how to use them for real-world NLP tasks, along with the skills to continue exploring this powerful technology independently. WHAT YOU WILL LEARN ● Learn Python, OpenAI, TensorFlow, Hugging Face, and vector databases. ● Master Python for NLP applications and data manipulation. ● Understand and implement GPT models for various tasks. ● Integrate GPT with various architectural components, such as databases, third-party APIs, servers, and data pipelines ● Utilise NLTK, PyTorch, and TensorFlow for advanced NLP projects. ● Use Jupyter for interactive coding and data analysis. WHO THIS BOOK IS FOR The Python GPT Cookbook is for IT professionals and business innovators who already have basic Python skills. Data scientists, ML engineers, NLP engineers, and ML researchers will also find it useful. TABLE OF CONTENTS 1. Introduction to GPT 2. Crafting Your GPT Workspace 3. Pre-processing 4. Embeddings 5. Classifying Intent 6. Hugging Face and GPT 7. Vector Databases 8. GPT, PyTorch, and TensorFlow 9. Custom GPT Actions 10. Integrating GPT with the Enterprise 11. Marketing and Sales with GPT 12. Intellectual Property Management with GPT 13. GPT in Manufacturing 14. Scaling up 15. Emerging Trends and Future Directions



Introduction To Python And Large Language Models


Introduction To Python And Large Language Models
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Author : Dilyan Grigorov
language : en
Publisher: Springer Nature
Release Date : 2024-10-22

Introduction To Python And Large Language Models written by Dilyan Grigorov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.


Gain a solid foundation for Natural Language Processing (NLP) and Large Language Models (LLMs), emphasizing their significance in today’s computational world. This book is an introductory guide to NLP and LLMs with Python programming. The book starts with the basics of NLP and LLMs. It covers essential NLP concepts, such as text preprocessing, feature engineering, and sentiment analysis using Python. The book offers insights into Python programming, covering syntax, data types, conditionals, loops, functions, and object-oriented programming. Next, it delves deeper into LLMs, unraveling their complex components. You’ll learn about LLM elements, including embedding layers, feedforward layers, recurrent layers, and attention mechanisms. You’ll also explore important topics like tokens, token distributions, zero-shot learning, LLM hallucinations, and insights into popular LLM architectures such as GPT-4, BERT, T5, PALM, and others. Additionally, it covers Python libraries like Hugging Face, OpenAI API, and Cohere. The final chapter bridges theory with practical application, offering step-by-step examples of coded applications for tasks like text generation, summarization, language translation, question-answering systems, and chatbots. In the end, this book will equip you with the knowledge and tools to navigate the dynamic landscape of NLP and LLMs. What You’ll Learn Understand the basics of Python and the features of Python 3.11 Explore the essentials of NLP and how do they lay the foundations for LLMs. Review LLM components. Develop basic apps using LLMs and Python. Who This Book Is For Data analysts, AI and Machine Learning Experts, Python developers, and Software Development Professionals interested in learning the foundations of NLP, LLMs, and the processes of building modern LLM applications for various tasks.



Llm Engineer S Handbook


Llm Engineer S Handbook
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Author : Paul Iusztin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-22

Llm Engineer S Handbook written by Paul Iusztin and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-22 with Computers categories.


Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Key Features Build and refine LLMs step by step, covering data preparation, RAG, and fine-tuning Learn essential skills for deploying and monitoring LLMs, ensuring optimal performance in production Utilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applications Book DescriptionArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems. Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects. By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.What you will learn Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine it with the help of hands-on examples Get started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring Perform supervised fine-tuning and LLM evaluation Deploy end-to-end LLM solutions using AWS and other tools Design scalable and modularLLM systems Learn about RAG applications by building a feature and inference pipeline Who this book is for This book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios



Mastering Transformers


Mastering Transformers
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Author : Savaş Yıldırım
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-06-03

Mastering Transformers written by Savaş Yıldırım and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-03 with Computers categories.


Explore transformer-based language models from BERT to GPT, delving into NLP and computer vision tasks, while tackling challenges effectively Key Features Understand the complexity of deep learning architecture and transformers architecture Create solutions to industrial natural language processing (NLP) and computer vision (CV) problems Explore challenges in the preparation process, such as problem and language-specific dataset transformation Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionTransformer-based language models such as BERT, T5, GPT, DALL-E, and ChatGPT have dominated NLP studies and become a new paradigm. Thanks to their accurate and fast fine-tuning capabilities, transformer-based language models have been able to outperform traditional machine learning-based approaches for many challenging natural language understanding (NLU) problems. Aside from NLP, a fast-growing area in multimodal learning and generative AI has recently been established, showing promising results. Mastering Transformers will help you understand and implement multimodal solutions, including text-to-image. Computer vision solutions that are based on transformers are also explained in the book. You’ll get started by understanding various transformer models before learning how to train different autoregressive language models such as GPT and XLNet. The book will also get you up to speed with boosting model performance, as well as tracking model training using the TensorBoard toolkit. In the later chapters, you’ll focus on using vision transformers to solve computer vision problems. Finally, you’ll discover how to harness the power of transformers to model time series data and for predicting. By the end of this transformers book, you’ll have an understanding of transformer models and how to use them to solve challenges in NLP and CV.What you will learn Focus on solving simple-to-complex NLP problems with Python Discover how to solve classification/regression problems with traditional NLP approaches Train a language model and explore how to fine-tune models to the downstream tasks Understand how to use transformers for generative AI and computer vision tasks Build transformer-based NLP apps with the Python transformers library Focus on language generation such as machine translation and conversational AI in any language Speed up transformer model inference to reduce latency Who this book is for This book is for deep learning researchers, hands-on practitioners, and ML/NLP researchers. Educators, as well as students who have a good command of programming subjects, knowledge in the field of machine learning and artificial intelligence, and who want to develop apps in the field of NLP as well as multimodal tasks will also benefit from this book’s hands-on approach. Knowledge of Python (or any programming language) and machine learning literature, as well as a basic understanding of computer science, are required.