Document Processing Using Machine Learning
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Document Processing Using Machine Learning
Document Processing Using Machine Learning aims at presenting a handful of resources for students and researchers working in the document image analysis (DIA) domain using machine learning since it covers multiple document processing problems. Starting with an explanation of how Artificial Intelligence (AI) plays an important role in this domain, the book further discusses how different machine learning algorithms can be applied for classification/recognition and clustering problems regardless the type of input data: images or text. In brief, the book offers comprehensive coverage of the most essential topics, including: · The role of AI for document image analysis · Optical character recognition · Machine learning algorithms for document analysis · Extreme learning machines and their applications · Mathematical foundation for Web text document analysis · Social media data analysis · Modalities for document dataset generation This book serves both undergraduate and graduate scholars in Computer Science/Information Technology/Electrical and Computer Engineering. Further, it is a great fit for early career research scientists and industrialists in the domain.
Deep Learning for Coders with fastai and PyTorch
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Intelligent Automation with IBM Cloud Pak for Business Automation
Leverage the low-code/no-code approach in IBM Cloud Pak for business automation to accelerate your organization's digital transformation Purchase of the print or Kindle book includes a free eBook PDF Key FeaturesGet a comprehensive understanding of IBM Cloud Pak for Business AutomationTake a deep dive into insights on RPA, workflow automation, and automated decisionsDeploy and manage production-grade automated solutions for scalability, stability, and performanceBook Description COVID-19 has made many businesses change how they work, change how they engage their customers, and even change their products. Several of these businesses have also recognized the need to make these changes within days as opposed to months or weeks. This has resulted in an unprecedented pace of digital transformation; and success, in many cases, depends on how quickly an organization can react to real-time decisions. This book begins by introducing you to IBM Cloud Pak for Business Automation, providing a hands-on approach to project implementation. As you progress through the chapters, you'll learn to take on business problems and identify the relevant technology and starting point. Next, you'll find out how to engage both the business and IT community to better understand business problems, as well as explore practical ways to start implementing your first automation project. In addition, the book will show you how to create task automation, interactive chatbots, workflow automation, and document processing. Finally, you'll discover deployment best practices that'll help you support highly available and resilient solutions. By the end of this book, you'll have a firm grasp on the types of business problems that can be solved with IBM Cloud Pak for Business Automation. What you will learnUnderstand key IBM automation technologies and learn how to apply them Cover the end-to-end journey of creating an automation solution from concept to deploymentUnderstand the features and capabilities of workflow, decisions, RPA, business applications, and document processing with AIAnalyze your business processes and discover automation opportunities with process miningSet up content management solutions that meet business, regulatory, and compliance needsUnderstand deployment environments supported by IBM Cloud Pak for Business AutomationWho this book is for This book is for robotic process automation (RPA) professionals and automation consultants who want to accelerate the digital transformation of their businesses using IBM automation. This book is also useful for solutions architects or enterprise architects looking for best practices to build resilient and scalable AI-driven automation solutions. A basic understanding of business processes, low-code visual modeling techniques, RPA, and AI concepts is assumed.