Next Gen Nlp With Transformers
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Next Gen Nlp With Transformers
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Author : Hollis Denning
language : en
Publisher: Independently Published
Release Date : 2025-08-11
Next Gen Nlp With Transformers written by Hollis Denning and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-11 with Computers categories.
Next-Gen NLP with Transformers: Practical Projects Using BERT, GPT, RAG, LoRA, Hugging Face & LangChain Master the latest transformer models and build real-world NLP applications - step-by-step. Are you ready to go beyond theory and start building cutting-edge Natural Language Processing (NLP) systems with confidence? This hands-on guide walks you through everything you need to deploy, fine-tune, and monitor real-world transformer pipelines using today's most powerful tools - including BERT, GPT, RAG, T5, LoRA, LangChain, FAISS, and Hugging Face. Whether you're a beginner, an ML practitioner, or a software engineer looking to break into AI-powered text systems, this book will give you the skills and tools to build production-grade applications from scratch. What You'll Learn - Practical, Modern, and Actionable Understand transformer models: BERT, GPT, T5, LLaMA, and more - explained clearly and practically. Fine-tune with LoRA: Apply parameter-efficient training to domain-specific tasks like legal text classification. Build RAG pipelines: Integrate FAISS or ChromaDB with GPT to create retrieval-augmented question-answering tools. Use LangChain like a pro: Create agents, prompt chains, memory modules, and custom tools. Deploy real apps: Use FastAPI, Docker, and Streamlit to launch apps on Render, Vercel, or GCP. Monitor and optimize: Track LLM usage, costs, and performance with LangSmith and PromptLayer. Inside the Book - Purely Practical Projects Build a Sentiment Classifier API with BERT + FastAPI Create a News Summarizer App with T5 + Streamlit Develop a Q&A Chatbot with GPT + LangChain memory Deploy a full AI Legal Assistant using RAG, LoRA, and private document search Implement Prompt Evaluation Sandboxes and CI/CD pipelines for LLM agents Perfect For: Beginners to Intermediate AI Engineers Python Developers Data Scientists Tech Founders Whether you're building chatbots, internal tools, or full-scale NLP products, this book offers a complete A-Z roadmap for turning transformer models into reliable, scalable, and intelligent applications. Bonus Content: Hugging Face Transformers Cheat Sheet LangChain Component Guide Dataset Repository for Legal, Financial, and Healthcare NLP Glossary of 100+ NLP Terms for Fast Reference Deployment Templates for FastAPI + Docker + Streamlit Don't just learn NLP - build it. Next-Gen NLP with Transformers gives you the clarity, confidence, and code to lead the AI future.
Mitigating Bias In Machine Learning
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Author : Carlotta A. Berry
language : en
Publisher: McGraw Hill Professional
Release Date : 2024-10-18
Mitigating Bias In Machine Learning written by Carlotta A. Berry and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-18 with Technology & Engineering categories.
This practical guide shows, step by step, how to use machine learning to carry out actionable decisions that do not discriminate based on numerous human factors, including ethnicity and gender. The authors examine the many kinds of bias that occur in the field today and provide mitigation strategies that are ready to deploy across a wide range of technologies, applications, and industries. Edited by engineering and computing experts, Mitigating Bias in Machine Learning includes contributions from recognized scholars and professionals working across different artificial intelligence sectors. Each chapter addresses a different topic and real-world case studies are featured throughout that highlight discriminatory machine learning practices and clearly show how they were reduced. Mitigating Bias in Machine Learning addresses: Ethical and Societal Implications of Machine Learning Social Media and Health Information Dissemination Comparative Case Study of Fairness Toolkits Bias Mitigation in Hate Speech Detection Unintended Systematic Biases in Natural Language Processing Combating Bias in Large Language Models Recognizing Bias in Medical Machine Learning and AI Models Machine Learning Bias in Healthcare Achieving Systemic Equity in Socioecological Systems Community Engagement for Machine Learning
Natural Language Processing With Transformers And Python
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Author : Raul Knotts
language : en
Publisher: Independently Published
Release Date : 2025-03-06
Natural Language Processing With Transformers And Python written by Raul Knotts and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-06 with Computers categories.
Natural Language Processing with Transformers and Python: Practical AI Solutions Overview Natural Language Processing (NLP) has transformed the way AI interacts with human language, and transformer models are at the heart of this revolution. Natural Language Processing with Transformers and Python: Practical AI Solutions provides a hands-on, practical guide to building powerful NLP applications using state-of-the-art transformer models. This book walks you through implementing, fine-tuning, and deploying transformers for tasks like text generation, sentiment analysis, chatbots, search engines, and more. Whether you're a beginner exploring NLP or an experienced developer looking to optimize your models, this guide offers real-world examples, step-by-step tutorials, and efficient coding practices to help you master transformers with Python. Starting with the basics of transformers and NLP fundamentals, this book gradually progresses to advanced model training, fine-tuning techniques, and real-world deployments. You'll learn how to work with popular libraries like Hugging Face Transformers, PyTorch, and TensorFlow, optimize models for speed and accuracy, and deploy them as APIs. Additionally, you'll explore cutting-edge topics such as Retrieval-Augmented Generation (RAG), semantic search, and multimodal AI. By the end of this book, you will have the skills to develop, customize, and scale NLP solutions that can process and understand human language with near-human accuracy. Key Features of This Book Hands-on NLP Projects - Implement real-world applications like chatbots, summarization, translation, and sentiment analysis. Fine-Tuning and Optimization - Learn how to fine-tune transformer models for domain-specific tasks and improve efficiency. Hugging Face and Python Ecosystem - Work with industry-standard tools and libraries to build and deploy transformer models. Deploying NLP Models - Convert models into APIs using FastAPI, Flask, and cloud platforms like Hugging Face Spaces & AWS Lambda. Emerging Trends - Explore multimodal AI, retrieval-augmented generation (RAG), and next-generation transformer architectures. This book is ideal for: Machine learning engineers and AI developers looking to integrate transformer models into real-world applications. Data scientists and NLP practitioners who want to fine-tune and deploy custom NLP solutions. Python programmers interested in learning the latest advancements in NLP with hands-on projects. Tech enthusiasts and researchers eager to explore modern AI trends and innovations in NLP. Unlock the power of transformers and Python to build cutting-edge NLP applications. Whether you're building chatbots, search engines, or text-generation models, this book provides everything you need to create intelligent AI-driven solutions.
Transformers For Natural Language Processing And Computer Vision
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Author : Denis Rothman
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-02-29
Transformers For Natural Language Processing And Computer Vision written by Denis Rothman 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 2024-02-29 with Computers categories.
The definitive guide to LLMs, from architectures, pretraining, and fine-tuning to Retrieval Augmented Generation (RAG), multimodal AI, risk mitigation, and practical implementations with ChatGPT, Hugging Face, and Vertex AI Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Compare and contrast 20+ models (including GPT, BERT, and Llama) and multiple platforms and libraries to find the right solution for your project Apply RAG with LLMs using customized texts and embeddings Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, practical applications, and popular platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through a range of transformer architectures from foundation models and generative AI. You’ll pretrain and fine-tune LLMs and work through different use cases, from summarization to question-answering systems leveraging embedding-based search. You'll also implement Retrieval Augmented Generation (RAG) to enhance accuracy and gain greater control over your LLM outputs. Additionally, you’ll understand common LLM risks, such as hallucinations, memorization, and privacy issues, and implement mitigation strategies using moderation models alongside rule-based systems and knowledge integration. Dive into generative vision transformers and multimodal architectures, and build practical applications, such as image and video classification. Go further and combine different models and platforms to build AI solutions and explore AI agent capabilities. This book provides you with an understanding of transformer architectures, including strategies for pretraining, fine-tuning, and LLM best practices.What you will learn Breakdown and understand the architectures of the Transformer, BERT, GPT, T5, PaLM, ViT, CLIP, and DALL-E Fine-tune BERT, GPT, and PaLM models Learn about different tokenizers and the best practices for preprocessing language data Pretrain a RoBERTa model from scratch Implement retrieval augmented generation and rules bases to mitigate hallucinations Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Go in-depth into vision transformers with CLIP, DALL-E, and GPT Who this book is for This book is ideal for NLP and CV engineers, data scientists, machine learning practitioners, software developers, and technical leaders looking to advance their expertise in LLMs and generative AI or explore latest industry trends. Familiarity with Python and basic machine learning concepts will help you fully understand the use cases and code examples. However, hands-on examples involving LLM user interfaces, prompt engineering, and no-code model building ensure this book remains accessible to anyone curious about the AI revolution.
Introduction To Transformers For Nlp
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Author : Shashank Mohan Jain
language : en
Publisher: Apress
Release Date : 2022-10-21
Introduction To Transformers For Nlp written by Shashank Mohan Jain and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Computers categories.
Get a hands-on introduction to Transformer architecture using the Hugging Face library. This book explains how Transformers are changing the AI domain, particularly in the area of natural language processing. This book covers Transformer architecture and its relevance in natural language processing (NLP). It starts with an introduction to NLP and a progression of language models from n-grams to a Transformer-based architecture. Next, it offers some basic Transformers examples using the Google colab engine. Then, it introduces the Hugging Face ecosystem and the different libraries and models provided by it. Moving forward, it explains language models such as Google BERT with some examples before providing a deep dive into Hugging Face API using different language models to address tasks such as sentence classification, sentiment analysis, summarization, and text generation. After completing Introduction to Transformers for NLP, you will understand Transformer concepts and be able to solve problems using the Hugging Face library. What You Will Learn Understand language models and their importance in NLP and NLU (Natural Language Understanding) Master Transformer architecture through practical examples Use the Hugging Face library in Transformer-based language models Create a simple code generator in Python based on Transformer architecture Who This Book Is ForData Scientists and software developers interested in developing their skills in NLP and NLU (Natural Language Understanding)
Mastering Transformers
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Author : Savaş Yıldırım
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-09-15
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 2021-09-15 with Computers categories.
Take a problem-solving approach to learning all about transformers and get up and running in no time by implementing methodologies that will build the future of NLP Key Features Explore quick prototyping with up-to-date Python libraries to create effective solutions to industrial problems Solve advanced NLP problems such as named-entity recognition, information extraction, language generation, and conversational AI Monitor your model's performance with the help of BertViz, exBERT, and TensorBoard Book DescriptionTransformer-based language models have dominated natural language processing (NLP) studies and have now become a new paradigm. With this book, you'll learn how to build various transformer-based NLP applications using the Python Transformers library. The book gives you an introduction to Transformers by showing you how to write your first hello-world program. You'll then learn how a tokenizer works and how to train your own tokenizer. As you advance, you'll explore the architecture of autoencoding models, such as BERT, and autoregressive models, such as GPT. You'll see how to train and fine-tune models for a variety of natural language understanding (NLU) and natural language generation (NLG) problems, including text classification, token classification, and text representation. This book also helps you to learn efficient models for challenging problems, such as long-context NLP tasks with limited computational capacity. You'll also work with multilingual and cross-lingual problems, optimize models by monitoring their performance, and discover how to deconstruct these models for interpretability and explainability. Finally, you'll be able to deploy your transformer models in a production environment. By the end of this NLP book, you'll have learned how to use Transformers to solve advanced NLP problems using advanced models.What you will learn Explore state-of-the-art NLP solutions with the Transformers library Train a language model in any language with any transformer architecture Fine-tune a pre-trained language model to perform several downstream tasks Select the right framework for the training, evaluation, and production of an end-to-end solution Get hands-on experience in using TensorBoard and Weights & Biases Visualize the internal representation of transformer models for interpretability Who this book is for This book is for deep learning researchers, hands-on NLP practitioners, as well as ML/NLP educators and students who want to start their journey with Transformers. Beginner-level machine learning knowledge and a good command of Python will help you get the best out of this book.
Dissertation Abstracts International
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Author :
language : en
Publisher:
Release Date : 2000
Dissertation Abstracts International written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Dissertations, Academic categories.
Electrical World
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Author :
language : en
Publisher:
Release Date : 1976
Electrical World written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Electrical engineering categories.
Index To Ieee Publications
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Author : Institute of Electrical and Electronics Engineers
language : en
Publisher:
Release Date : 1995
Index To Ieee Publications written by Institute of Electrical and Electronics Engineers and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Electrical engineering categories.
Whitaker S Cumulative Book List
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Author :
language : en
Publisher:
Release Date : 1985
Whitaker S Cumulative Book List written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Great Britain categories.