Download or read book Real World Asset Tokenization written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-09-04 with total page 74 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Real World Asset Tokenization" delves into the cutting-edge world of digital finance, where blockchain technology is revolutionizing asset ownership and investment. This comprehensive guide explores the process of tokenizing tangible and intangible assets, offering insights into the legal, technical, and economic aspects of this transformative trend. With real-world case studies and a focus on future innovations, this book provides valuable knowledge for investors, businesses, and regulators seeking to navigate the dynamic landscape of asset tokenization. Discover how tokenization is democratizing access to investments, enhancing liquidity, and reshaping the financial ecosystem. asset tokenization, blockchain technology, digital assets, smart contracts, real estate tokenization, financial innovation, decentralized finance, regulatory compliance, market liquidity, investment opportunities

Download or read book Tokenized Trillions written by Heath Muchena and published by . This book was released on 2020-06-03 with total page 52 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is a comprehensive guide to help you understand blockchain technology and how to determine business requirements essential for token model creation with respect to real-world asset tokenization projects.Some of the questions the book hopes to answer include: What is Blockchain? A Brief History How does blockchain technology work?What are the benefits of blockchain-based innovations?What exactly is asset tokenization?Why make an asset-backed token?What are the main asset-backed token categories?What are some examples of asset-backed token use cases?What is debt and equity tokenization (VC fund, private equity, real estate, private company shares)?Can commodities be tokenized?What are digital asset collectibles?What are some examples of non-fungible soft asset tokenization/ intellectual property tokenization?What is the future of hard asset tokenization - e.g. tokenization of real estate?What are some of the opportunities and challenges for security tokens?What will asset tokenization contribute to delivery of use-cases?What resources are required to securitize real-world assets using blockchain?What changes can be envisaged in service models?What new services and capabilities will maximise the benefit of distributed ledger technology for investors?What cost savings can be achieved?What service level improvements will be delivered to clients?What new products are going to be delivered that specifically exploit blockchain technology? How are workflows going to be modified on existing products to deal with the reengineered client processes and disintermediation of established entities that are facilitated by blockchain?How will blockchain technology affect existing real-world investment products

Download or read book Python Real World Machine Learning written by Prateek Joshi and published by Packt Publishing Ltd. This book was released on 2016-11-14 with total page 941 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to solve challenging data science problems by building powerful machine learning models using Python About This Book Understand which algorithms to use in a given context with the help of this exciting recipe-based guide This practical tutorial tackles real-world computing problems through a rigorous and effective approach Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected. What You Will Learn Use predictive modeling and apply it to real-world problems Understand how to perform market segmentation using unsupervised learning Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms Increase predictive accuracy with deep learning and scalable data-handling techniques Work with modern state-of-the-art large-scale machine learning techniques Learn to use Python code to implement a range of machine learning algorithms and techniques In Detail Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python Machine Learning Cookbook by Prateek Joshi Advanced Machine Learning with Python by John Hearty Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron Style and approach This course is a smooth learning path that will teach you how to get started with Python machine learning for the real world, and develop solutions to real-world problems. Through this comprehensive course, you'll learn to create the most effective machine learning techniques from scratch and more!

Download or read book Tokenizing the World written by Gwendolyn Lee and published by Independently Published. This book was released on 2023-08-08 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Tokenizing the World: The Shift from Traditional Assets to Blockchain-Based Tokens" is an all-encompassing report that offers a thorough yet lucid exploration of the groundbreaking shift from traditional assets to the emerging world of blockchain-based tokens. This enlightening guide offers original insights and reader-friendly analysis, making it an unparalleled resource for anyone looking to grasp the essence of digital assets. In the passionately crafted narrative of this Special Report, author Gwendolyn Lee removes the layer of intimidating jargon that often accompanies cryptocurrency discourse, replacing it with digestible, engaging, and enriching narratives. Gwendolyn's unique style simplifies complex themes, providing an enriching dive into the deep seas of blockchain networks, digital assets, and tokenization. Packed within this report are: An easily understandable introduction to the blockchain phenomenon A comparative analysis of traditional and digital assets Comprehensive knowledge on tokenization The saga of the evolution of cryptocurrencies Insights on the impact of blockchain tokens on the global economy Guidance on the legal and regulatory aspects of tokenization Discussion on the security measures in a tokenized world A glimpse into the potential future of asset ownership through tokenization An in-depth exploration of investing in blockchain-based tokens Thoughts on the evolving trends of tokenization in an unfolding future Purchasing this Special Report could be seen as the first enlightening step towards grasping the world of digital assets. Walk hand in hand with the author as she guides you through the thrilling labyrinth of blockchain, and emerge with a newfound appreciation for this innovative landscape. Prepare to unravel the mysteries of the blockchain era and engage with the future of finance. Unveil the promising world of digital assets with "Tokenizing the World."

Download or read book The Essential Guide to Web3 written by Vijay Krishnan and published by Packt Publishing Ltd. This book was released on 2023-11-30 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get up and running with blockchain, smart contracts, NFTs, DAOs, and decentralization in no time with the help of this comprehensive guide Key Features Get to grips with Web3, NFTs, DeFi, and smart contract development Create fungible and non-fungible tokens, explore DAOs, and more Build powerful apps using Ethereum to secure transactions and create smart contracts Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionWeb3, the new blockchain-based web, is often hailed as the future of the internet. Driven by technologies such as cryptocurrencies, NFTs, DAOs, decentralized finance, and more, Web3’s aim is to give individuals more control over the web communities they belong to. Whether you’re a beginner or an experienced developer, this book will help you master the intricacies of Web3 and its revolutionary technologies. Beginning with a concise introduction to blockchain and the Ethereum ecosystem, this book quickly immerses you in real-world blockchain applications. You’ll work on carefully crafted hands-on exercises that are designed for beginners as well as users with prior exposure. The chapters show you how to build and deploy smart contracts, while mastering security controls and discovering best practices for writing secure code. As you progress, you’ll explore tokenization and gain proficiency in minting both fungible and non-fungible tokens (NFTs) with the help of step-by-step instructions. The concluding chapters cover advanced topics, including oracles, Layer 2 (L2) networks, rollups, zero knowledge proofs, and decentralized autonomous organizations (DAOs). By the end of this Web3 book, you’ll be well-versed in the Web3 ecosystem and have the skills to build powerful and secure decentralized applications.What you will learn Get an in-depth understanding of Ethereum's ecosystem, its status, and key EIPs and ERCs Gain practical skills using non-custodial wallets such as MetaMask for blockchain transactions Write, debug, and deploy smart contracts on test networks Discover Web3 dev tools and set up a local environment Get to grips with tokenomics and create ERC20, ERC721, and ERC1155 tokens Explore decentralized storage with IPFS and integrate it into your Web3 projects Expand your NFT strategy with APIs and SDKs to lead in the NFT space Who this book is for This book is for blockchain developers and blockchain enthusiasts who want to build powerful and secure decentralized applications. Familiarity with the basics of blockchain, along with knowledge of how they function, is necessary to grasp the topics discussed in this book.

Download or read book Natural Language Processing in the Real World written by Jyotika Singh and published by CRC Press. This book was released on 2023-07-03 with total page 393 pages. Available in PDF, EPUB and Kindle. Book excerpt: Natural Language Processing in the Real World is a practical guide for applying data science and machine learning to build Natural Language Processing (NLP) solutions. Where traditional, academic-taught NLP is often accompanied by a data source or dataset to aid solution building, this book is situated in the real world where there may not be an existing rich dataset. This book covers the basic concepts behind NLP and text processing and discusses the applications across 15 industry verticals. From data sources and extraction to transformation and modelling, and classic Machine Learning to Deep Learning and Transformers, several popular applications of NLP are discussed and implemented. This book provides a hands-on and holistic guide for anyone looking to build NLP solutions, from students of Computer Science to those involved in large-scale industrial projects.

Download or read book Natural Language Processing with Spark NLP written by Alex Thomas and published by "O'Reilly Media, Inc.". This book was released on 2020-06-25 with total page 411 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you want to build an enterprise-quality application that uses natural language text but aren’t sure where to begin or what tools to use, this practical guide will help get you started. Alex Thomas, principal data scientist at Wisecube, shows software engineers and data scientists how to build scalable natural language processing (NLP) applications using deep learning and the Apache Spark NLP library. Through concrete examples, practical and theoretical explanations, and hands-on exercises for using NLP on the Spark processing framework, this book teaches you everything from basic linguistics and writing systems to sentiment analysis and search engines. You’ll also explore special concerns for developing text-based applications, such as performance. In four sections, you’ll learn NLP basics and building blocks before diving into application and system building: Basics: Understand the fundamentals of natural language processing, NLP on Apache Stark, and deep learning Building blocks: Learn techniques for building NLP applications—including tokenization, sentence segmentation, and named-entity recognition—and discover how and why they work Applications: Explore the design, development, and experimentation process for building your own NLP applications Building NLP systems: Consider options for productionizing and deploying NLP models, including which human languages to support

Download or read book Build a Large Language Model From Scratch written by Sebastian Raschka and published by Simon and Schuster. This book was released on 2024-10-29 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up! In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks. Build a Large Language Model (from Scratch) teaches you how to: • Plan and code all the parts of an LLM • Prepare a dataset suitable for LLM training • Fine-tune LLMs for text classification and with your own data • Use human feedback to ensure your LLM follows instructions • Load pretrained weights into an LLM Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant. Purchase of the print book includes a free eBook in PDF and ePub formats from Manning Publications. About the technology Physicist Richard P. Feynman reportedly said, “I don’t understand anything I can’t build.” Based on this same powerful principle, bestselling author Sebastian Raschka guides you step by step as you build a GPT-style LLM that you can run on your laptop. This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning. About the book Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself! What's inside • Plan and code an LLM comparable to GPT-2 • Load pretrained weights • Construct a complete training pipeline • Fine-tune your LLM for text classification • Develop LLMs that follow human instructions About the reader Readers need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs. About the author Sebastian Raschka is a Staff Research Engineer at Lightning AI, where he works on LLM research and develops open-source software. The technical editor on this book was David Caswell. Table of Contents 1 Understanding large language models 2 Working with text data 3 Coding attention mechanisms 4 Implementing a GPT model from scratch to generate text 5 Pretraining on unlabeled data 6 Fine-tuning for classification 7 Fine-tuning to follow instructions A Introduction to PyTorch B References and further reading C Exercise solutions D Adding bells and whistles to the training loop E Parameter-efficient fine-tuning with LoRA

Download or read book Blockchain Banking written by Monty C. M. Metzger and published by BoD – Books on Demand. This book was released on 2023-01-16 with total page 370 pages. Available in PDF, EPUB and Kindle. Book excerpt: Blockchain is not just a technology, it is a groundbreaking concept for decentralized money and finance. Monty Metzger has done something really important: showcasing the business impact of that concept, revealing just how revolutionary it is. In a book that is one part prophecy and future research report, one part documentation and case studies, and one part survival manual, internet entrepreneur and thought leader Monty C. M. Metzger showcases the impact of Blockchain on finance and money, to discover seven leadership opportunities and straight forward rules for every digital leader. At the same time, he illuminates the new financial order of the internet of value: how it challenges and destroys the status quo but also opens up new areas of innovation. His findings are counterintuitive, imaginative, practical, and above all visionary, giving readers a glimpse of how everyone and everything - from corporations to governments, nations to individuals - must evolve in the blockchain era. Blockchain Banking is an astonishing, mind-opening book that, in the end, is not about technology. It is about you. - "Blockchain is not just a technology, it is a groundbreaking concept for decentralized money and finance. Monty Metzger has done something really important: showcasing the impact of that concept, revealing just how revolutionary it is" "Blockchain Banking is a must-read for anyone looking to understand the opportunities and challenges of using blockchain technology in the financial industry. The book provides a clear and concise overview of the key concepts, and offers valuable insights into how businesses can use blockchain to create new, more efficient and more secure financial services." "Blockchain Banking is a thought-provoking and timely book that offers a fresh perspective on the future of finance. Monty's deep knowledge of the industry and clear writing style make it a must-read for anyone interested in the intersection of blockchain and banking."

Download or read book Applied Natural Language Processing in the Enterprise written by Ankur A. Patel and published by "O'Reilly Media, Inc.". This book was released on 2021-05-12 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: NLP has exploded in popularity over the last few years. But while Google, Facebook, OpenAI, and others continue to release larger language models, many teams still struggle with building NLP applications that live up to the hype. This hands-on guide helps you get up to speed on the latest and most promising trends in NLP. With a basic understanding of machine learning and some Python experience, you'll learn how to build, train, and deploy models for real-world applications in your organization. Authors Ankur Patel and Ajay Uppili Arasanipalai guide you through the process using code and examples that highlight the best practices in modern NLP. Use state-of-the-art NLP models such as BERT and GPT-3 to solve NLP tasks such as named entity recognition, text classification, semantic search, and reading comprehension Train NLP models with performance comparable or superior to that of out-of-the-box systems Learn about Transformer architecture and modern tricks like transfer learning that have taken the NLP world by storm Become familiar with the tools of the trade, including spaCy, Hugging Face, and fast.ai Build core parts of the NLP pipeline--including tokenizers, embeddings, and language models--from scratch using Python and PyTorch Take your models out of Jupyter notebooks and learn how to deploy, monitor, and maintain them in production

Download or read book Relevant Search written by John Berryman and published by Simon and Schuster. This book was released on 2016-06-19 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Relevant Search demystifies relevance work. Using Elasticsearch, it teaches you how to return engaging search results to your users, helping you understand and leverage the internals of Lucene-based search engines. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Users are accustomed to and expect instant, relevant search results. To achieve this, you must master the search engine. Yet for many developers, relevance ranking is mysterious or confusing. About the Book Relevant Search demystifies the subject and shows you that a search engine is a programmable relevance framework. You'll learn how to apply Elasticsearch or Solr to your business's unique ranking problems. The book demonstrates how to program relevance and how to incorporate secondary data sources, taxonomies, text analytics, and personalization. In practice, a relevance framework requires softer skills as well, such as collaborating with stakeholders to discover the right relevance requirements for your business. By the end, you'll be able to achieve a virtuous cycle of provable, measurable relevance improvements over a search product's lifetime. What's Inside Techniques for debugging relevance? Applying search engine features to real problems? Using the user interface to guide searchers? A systematic approach to relevance? A business culture focused on improving search About the Reader For developers trying to build smarter search with Elasticsearch or Solr. About the Authors Doug Turnbull is lead relevance consultant at OpenSource Connections, where he frequently speaks and blogs. John Berryman is a data engineer at Eventbrite, where he specializes in recommendations and search. Foreword author, Trey Grainger, is a director of engineering at CareerBuilder and author of Solr in Action. Table of Contents The search relevance problem Search under the hood Debugging your first relevance problem Taming tokens Basic multifield search Term-centric search Shaping the relevance function Providing relevance feedback Designing a relevance-focused search application The relevance-centered enterprise Semantic and personalized search

Download or read book Supervised Machine Learning for Text Analysis in R written by Emil Hvitfeldt and published by CRC Press. This book was released on 2021-10-22 with total page 402 pages. Available in PDF, EPUB and Kindle. Book excerpt: Text data is important for many domains, from healthcare to marketing to the digital humanities, but specialized approaches are necessary to create features for machine learning from language. Supervised Machine Learning for Text Analysis in R explains how to preprocess text data for modeling, train models, and evaluate model performance using tools from the tidyverse and tidymodels ecosystem. Models like these can be used to make predictions for new observations, to understand what natural language features or characteristics contribute to differences in the output, and more. If you are already familiar with the basics of predictive modeling, use the comprehensive, detailed examples in this book to extend your skills to the domain of natural language processing. This book provides practical guidance and directly applicable knowledge for data scientists and analysts who want to integrate unstructured text data into their modeling pipelines. Learn how to use text data for both regression and classification tasks, and how to apply more straightforward algorithms like regularized regression or support vector machines as well as deep learning approaches. Natural language must be dramatically transformed to be ready for computation, so we explore typical text preprocessing and feature engineering steps like tokenization and word embeddings from the ground up. These steps influence model results in ways we can measure, both in terms of model metrics and other tangible consequences such as how fair or appropriate model results are.

Download or read book Revolutionizing Finance written by Livewire Money and published by Independently Published. This book was released on 2024-06-17 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the future of finance with "Revolutionizing Finance: Create Wealth with Real World Asset Tokenization". This comprehensive guide provides everything you need to understand and leverage the transformative power of asset tokenization. In this book, Livewire Money demystifies the complex world of tokenization, breaking down its principles, benefits, and applications across various asset classes. From real estate and commodities to art and collectibles, discover how tokenization can increase liquidity, enable fractional ownership, reduce transaction costs, and enhance transparency and security. Explore the step-by-step process of tokenizing assets, including identifying and valuing assets, legal and regulatory considerations, creating digital tokens, and managing tokenized assets post-listing. Gain insights from real-world case studies that highlight successful tokenization projects and their impact. Navigate the legal and regulatory landscape with confidence, understanding global frameworks, jurisdictional challenges, and compliance measures. Delve into the technology behind tokenization, including blockchain platforms, smart contracts, and security token standards. Develop effective investment strategies with tokenized assets, learning how to diversify your portfolio, generate passive income, and manage risks. Understand the challenges and risks associated with asset tokenization, from technological and market risks to legal and valuation issues. Look ahead to the future of asset tokenization with emerging trends, potential impacts on global financial markets, and integration with traditional financial systems. Get practical advice for both asset owners and investors on how to successfully navigate this evolving landscape. Whether you're a seasoned investor, a financial professional, or someone new to the concept of asset tokenization, "Revolutionizing Finance" offers valuable insights and practical guidance to help you create wealth in this new frontier of finance. Transform your understanding of asset management and investment with this essential guide to real world asset tokenization.

Download or read book EQUITY TOKENIZATION Empower your Fundraising Unlock new blockchain possibilities written by Yassir Haouati and published by Yassir Haouati. This book was released on with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: Empower Your Business Fundraising Strategy with Equity Tokenization! In today's digital age, the potential for fundraising has skyrocketed. With Equity Tokenization, you can harness the power of blockchain technology to unlock new possibilities for your business. Say goodbye to traditional fundraising limitations and embrace a decentralized and transparent approach that brings together global investors and empowers startups like never before. This guide dives deep into the world of tokenization, providing invaluable insights into the legal, regulatory, and economic aspects of tokenized equity. Take charge of your fundraising journey and optimize your token ecosystem with expert strategies for token design, distribution, governance, and voting rights. Revolutionize Fundraising: Discover how blockchain technology is transforming the fundraising landscape, offering enhanced liquidity, global investor reach, and increased market efficiency. Learn how tokenized equity empowers businesses to democratize investment opportunities and create a thriving community of investors. Navigate the Legal Landscape: Don't let legal complexities hold you back. Uncover valuable insights into the regulatory considerations and legal frameworks for equity tokenization. Explore intellectual property, licensing, and the role of smart contracts in ensuring legal enforceability. Optimize Tokenomics: The economic framework of tokens is critical to success. Dive into token design, distribution strategies, governance, and voting rights. Discover the relationship between tokenomics and business models to create a robust token ecosystem. Craft Your Equity Token Whitepaper: Your whitepaper is your beacon of credibility. Master the art of creating a compelling whitepaper with problem statements, project overviews, token details, and more. Build investor confidence, identify risks, and implement effective risk mitigation strategies. Supercharge Marketing Strategies: Elevate your marketing game with data-driven strategies. Understand your target audience, create engaging materials, run digital advertising campaigns, and leverage influencer marketing. Learn the art of community building and engagement. Whether you're a seasoned entrepreneur or a curious mind seeking to embrace the future of fundraising, this book is your guide to navigating the complexities of equity tokenization successfully. Unleash the true potential of your fundraising endeavors and redefine ownership in the decentralized world. It's time to make an impact—unlock new horizons today!

Download or read book Hands On Large Language Models written by Jay Alammar and published by "O'Reilly Media, Inc.". This book was released on 2024-09-11 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI has acquired startling new language capabilities in just the past few years. Driven by the rapid advances in deep learning, language AI systems are able to write and understand text better than ever before. This trend enables the rise of new features, products, and entire industries. With this book, Python developers will learn the practical tools and concepts they need to use these capabilities today. You'll learn how to use the power of pre-trained large language models for use cases like copywriting and summarization; create semantic search systems that go beyond keyword matching; build systems that classify and cluster text to enable scalable understanding of large amounts of text documents; and use existing libraries and pre-trained models for text classification, search, and clusterings. This book also shows you how to: Build advanced LLM pipelines to cluster text documents and explore the topics they belong to Build semantic search engines that go beyond keyword search with methods like dense retrieval and rerankers Learn various use cases where these models can provide value Understand the architecture of underlying Transformer models like BERT and GPT Get a deeper understanding of how LLMs are trained Understanding how different methods of fine-tuning optimize LLMs for specific applications (generative model fine-tuning, contrastive fine-tuning, in-context learning, etc.)

Download or read book Machine Learning Infrastructure and Best Practices for Software Engineers written by Miroslaw Staron and published by Packt Publishing Ltd. This book was released on 2024-01-31 with total page 346 pages. Available in PDF, EPUB and Kindle. Book excerpt: Efficiently transform your initial designs into big systems by learning the foundations of infrastructure, algorithms, and ethical considerations for modern software products Key Features Learn how to scale-up your machine learning software to a professional level Secure the quality of your machine learning pipeline at runtime Apply your knowledge to natural languages, programming languages, and images Book DescriptionAlthough creating a machine learning pipeline or developing a working prototype of a software system from that pipeline is easy and straightforward nowadays, the journey toward a professional software system is still extensive. This book will help you get to grips with various best practices and recipes that will help software engineers transform prototype pipelines into complete software products. The book begins by introducing the main concepts of professional software systems that leverage machine learning at their core. As you progress, you’ll explore the differences between traditional, non-ML software, and machine learning software. The initial best practices will guide you in determining the type of software you need for your product. Subsequently, you will delve into algorithms, covering their selection, development, and testing before exploring the intricacies of the infrastructure for machine learning systems by defining best practices for identifying the right data source and ensuring its quality. Towards the end, you’ll address the most challenging aspect of large-scale machine learning systems – ethics. By exploring and defining best practices for assessing ethical risks and strategies for mitigation, you will conclude the book where it all began – large-scale machine learning software.What you will learn Identify what the machine learning software best suits your needs Work with scalable machine learning pipelines Scale up pipelines from prototypes to fully fledged software Choose suitable data sources and processing methods for your product Differentiate raw data from complex processing, noting their advantages Track and mitigate important ethical risks in machine learning software Work with testing and validation for machine learning systems Who this book is for If you’re a machine learning engineer, this book will help you design more robust software, and understand which scaling-up challenges you need to address and why. Software engineers will benefit from best practices that will make your products robust, reliable, and innovative. Decision makers will also find lots of useful information in this book, including guidance on what to look for in a well-designed machine learning software product.

Download or read book Natural Language Processing with Transformers Revised Edition written by Lewis Tunstall and published by "O'Reilly Media, Inc.". This book was released on 2022-05-26 with total page 409 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 transformers work and how to integrate them in your applications. You'll quickly learn a variety of tasks they can help you solve. Build, debug, and optimize transformer models for core NLP tasks, such as text classification, named entity recognition, and question answering Learn how transformers can be used for cross-lingual transfer learning Apply transformers in real-world scenarios where labeled data is scarce Make transformer models efficient for deployment using techniques such as distillation, pruning, and quantization Train transformers from scratch and learn how to scale to multiple GPUs and distributed environments