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Mastering Transformers - Second Edition
With this NLP transformers book, you'll be able to implement multimodal solutions, including text-to-image (Stable Diffusion).
Mastering Transformers
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-tun...
Mastering Transformers
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 trans...
Python Feature Engineering Cookbook
Leverage the power of Python to build real-world feature engineering and machine learning pipelines ready to be deployed to production Key Features Learn Craft powerful features from tabular, transactional, and time-series data Develop efficient and reproducible real-world feature engineering pipelines Optimize data transformation and save valuable time Purchase of the print or Kindle book includes a free PDF eBook Book Description Streamline data preprocessing and feature engineering in your machine learning project with this third edition of the Python Feature Engineering Cookbook to make your data preparation more efficient. This guide addresses common challenges, such as imputing missing...
ECAI 2023
Artificial intelligence, or AI, now affects the day-to-day life of almost everyone on the planet, and continues to be a perennial hot topic in the news. This book presents the proceedings of ECAI 2023, the 26th European Conference on Artificial Intelligence, and of PAIS 2023, the 12th Conference on Prestigious Applications of Intelligent Systems, held from 30 September to 4 October 2023 and on 3 October 2023 respectively in Kraków, Poland. Since 1974, ECAI has been the premier venue for presenting AI research in Europe, and this annual conference has become the place for researchers and practitioners of AI to discuss the latest trends and challenges in all subfields of AI, and to demonstrat...
Transformers for Natural Language Processing
Publisher's Note: A new edition of this book is out now that includes working with GPT-3 and comparing the results with other models. It includes even more use cases, such as casual language analysis and computer vision tasks, as well as an introduction to OpenAI's Codex. Key FeaturesBuild and implement state-of-the-art language models, such as the original Transformer, BERT, T5, and GPT-2, using concepts that outperform classical deep learning modelsGo through hands-on applications in Python using Google Colaboratory Notebooks with nothing to install on a local machineTest transformer models on advanced use casesBook Description The transformer architecture has proved to be revolutionary in...
Optical Code Division Multiple Access
Code-division multiple access (CDMA) technology has been widely adopted in cell phones. Its astonishing success has led many to evaluate the promise of this technology for optical networks. This field has come to be known as Optical CDMA (OCDMA). Surveying the field from its infancy to the current state, Optical Code Division Multiple Access: Fundamentals and Applications offers the first comprehensive treatment of OCDMA from technology to systems. The book opens with a historical perspective, demonstrating the growth and development of the technologies that would eventually evolve into today's optical networks. Building on this background, the discussion moves to coherent and incoherent opt...
Natural Language Processing with Transformers, Revised Edition
Since their introduction in 2017, transformers have quickly become the dominant architecture for achieving state-of-the-art results on a variety of natural language processing tasks. If you're a data scientist or coder, this practical book -now revised in full color- shows you how to train and scale these large models using Hugging Face Transformers, a Python-based deep learning library. Transformers have been used to write realistic news stories, improve Google Search queries, and even create chatbots that tell corny jokes. In this guide, authors Lewis Tunstall, Leandro von Werra, and Thomas Wolf, among the creators of Hugging Face Transformers, use a hands-on approach to teach you how tran...
Getting Started with Google BERT
Kickstart your NLP journey by exploring BERT and its variants such as ALBERT, RoBERTa, DistilBERT, VideoBERT, and more with Hugging Face's transformers library Key FeaturesExplore the encoder and decoder of the transformer modelBecome well-versed with BERT along with ALBERT, RoBERTa, and DistilBERTDiscover how to pre-train and fine-tune BERT models for several NLP tasksBook Description BERT (bidirectional encoder representations from transformer) has revolutionized the world of natural language processing (NLP) with promising results. This book is an introductory guide that will help you get to grips with Google's BERT architecture. With a detailed explanation of the transformer architecture...
Deep Learning-Based Approaches for Sentiment Analysis
This book covers deep-learning-based approaches for sentiment analysis, a relatively new, but fast-growing research area, which has significantly changed in the past few years. The book presents a collection of state-of-the-art approaches, focusing on the best-performing, cutting-edge solutions for the most common and difficult challenges faced in sentiment analysis research. Providing detailed explanations of the methodologies, the book is a valuable resource for researchers as well as newcomers to the field.
