Download or read book The Language Architect Building the Future with Mistral LLM written by Anand Vemula and published by Anand Vemula. This book was released on with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Language Architect: Building the Future with Mistral LLM Unlock the potential of language and co-create the future with Mistral LLM, a revolutionary large language model. In "The Language Architect: Building the Future with Mistral LLM," you'll embark on a journey into the exciting world of large language models (LLMs) and delve into the capabilities of Mistral LLM, a powerful AI tool that's shaping the future of communication. This book is your comprehensive guide to understanding Mistral LLM. You'll explore its inner workings, from its innovative architecture to its impressive multilingual abilities. Master the Fundamentals: Gain a solid understanding of LLMs and how they revolutionize human-computer interaction. Dive into Mistral LLM: Explore the technical aspects of Mistral, including its decoder-only transformer model, efficiency techniques, and training processes. Unleash the Power of Words: Discover how Mistral LLM can generate creative text formats, translate languages with accuracy, and answer your questions in informative ways. Become a Language Architect: Learn how to leverage Mistral LLM for various applications, from crafting compelling content to creating chatbots and virtual assistants. But "The Language Architect" goes beyond just technical understanding. It emphasizes the responsible development and use of LLMs. Navigate Ethical Considerations: Explore the potential biases and limitations of LLMs and how Mistral prioritizes safety and ethical AI practices. Forge a Human-Machine Partnership: Discover how to collaborate with Mistral LLM to achieve exceptional results while ensuring responsible use of this powerful technology. This book is for anyone interested in the future of language and AI. Whether you're a writer, programmer, entrepreneur, or simply curious about technological advancements, "The Language Architect" equips you with the knowledge and insights to become a co-architect of the future, working alongside Mistral LLM to unlock its potential for positive change.

Download or read book Driving Digital Strategy written by Sunil Gupta and published by Harvard Business Press. This book was released on 2018-07-24 with total page 327 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital transformation is no longer news--it's a necessity. Despite the widespread threat of disruption, many large companies in traditional industries have succeeded at digitizing their businesses in truly transformative ways. The New York Times, formerly a bastion of traditional media, has created a thriving digital product behind a carefully designed paywall. Best Buy has transformed its business in the face of Amazon's threat. John Deere has formed a data-analysis arm to complement its farm-equipment business. And Goldman Sachs and many others are using digital technologies to reimagine their businesses. In Driving Digital Strategy, Harvard Business School professor Sunil Gupta provides an actionable framework for following their lead. For over a decade, Gupta has studied digital transformation at Fortune 500 companies. He knows what works and what doesn't. Merely dabbling in digital or launching a small independent unit, which many companies do, will not bring success. Instead you need to fundamentally change the core of your business and ensure that your digital strategy touches all aspects of your organization: your business model, value chain, customer relationships, and company culture. Gupta covers each aspect in vivid detail while providing navigation tips and best practices along the way. Filled with rich and illuminating case studies of companies at the forefront of digital transformation, Driving Digital Strategy is the comprehensive guide you need to take full advantage of the limitless opportunities the digital age provides.

Download or read book Artificial Intelligence with Python Cookbook written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2020-10-30 with total page 459 pages. Available in PDF, EPUB and Kindle. Book excerpt: Work through practical recipes to learn how to solve complex machine learning and deep learning problems using Python Key FeaturesGet up and running with artificial intelligence in no time using hands-on problem-solving recipesExplore popular Python libraries and tools to build AI solutions for images, text, sounds, and imagesImplement NLP, reinforcement learning, deep learning, GANs, Monte-Carlo tree search, and much moreBook Description Artificial intelligence (AI) plays an integral role in automating problem-solving. This involves predicting and classifying data and training agents to execute tasks successfully. This book will teach you how to solve complex problems with the help of independent and insightful recipes ranging from the essentials to advanced methods that have just come out of research. Artificial Intelligence with Python Cookbook starts by showing you how to set up your Python environment and taking you through the fundamentals of data exploration. Moving ahead, you’ll be able to implement heuristic search techniques and genetic algorithms. In addition to this, you'll apply probabilistic models, constraint optimization, and reinforcement learning. As you advance through the book, you'll build deep learning models for text, images, video, and audio, and then delve into algorithmic bias, style transfer, music generation, and AI use cases in the healthcare and insurance industries. Throughout the book, you’ll learn about a variety of tools for problem-solving and gain the knowledge needed to effectively approach complex problems. By the end of this book on AI, you will have the skills you need to write AI and machine learning algorithms, test them, and deploy them for production. What you will learnImplement data preprocessing steps and optimize model hyperparametersDelve into representational learning with adversarial autoencodersUse active learning, recommenders, knowledge embedding, and SAT solversGet to grips with probabilistic modeling with TensorFlow probabilityRun object detection, text-to-speech conversion, and text and music generationApply swarm algorithms, multi-agent systems, and graph networksGo from proof of concept to production by deploying models as microservicesUnderstand how to use modern AI in practiceWho this book is for This AI machine learning book is for Python developers, data scientists, machine learning engineers, and deep learning practitioners who want to learn how to build artificial intelligence solutions with easy-to-follow recipes. You’ll also find this book useful if you’re looking for state-of-the-art solutions to perform different machine learning tasks in various use cases. Basic working knowledge of the Python programming language and machine learning concepts will help you to work with code effectively in this book.

Download or read book Machine Learning for Time Series with Python written by Ben Auffarth and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get better insights from time-series data and become proficient in model performance analysis Key FeaturesExplore popular and modern machine learning methods including the latest online and deep learning algorithmsLearn to increase the accuracy of your predictions by matching the right model with the right problemMaster time series via real-world case studies on operations management, digital marketing, finance, and healthcareBook Description The Python time-series ecosystem is huge and often quite hard to get a good grasp on, especially for time-series since there are so many new libraries and new models. This book aims to deepen your understanding of time series by providing a comprehensive overview of popular Python time-series packages and help you build better predictive systems. Machine Learning for Time-Series with Python starts by re-introducing the basics of time series and then builds your understanding of traditional autoregressive models as well as modern non-parametric models. By observing practical examples and the theory behind them, you will become confident with loading time-series datasets from any source, deep learning models like recurrent neural networks and causal convolutional network models, and gradient boosting with feature engineering. This book will also guide you in matching the right model to the right problem by explaining the theory behind several useful models. You'll also have a look at real-world case studies covering weather, traffic, biking, and stock market data. By the end of this book, you should feel at home with effectively analyzing and applying machine learning methods to time-series. What you will learnUnderstand the main classes of time series and learn how to detect outliers and patternsChoose the right method to solve time-series problemsCharacterize seasonal and correlation patterns through autocorrelation and statistical techniquesGet to grips with time-series data visualizationUnderstand classical time-series models like ARMA and ARIMAImplement deep learning models, like Gaussian processes, transformers, and state-of-the-art machine learning modelsBecome familiar with many libraries like Prophet, XGboost, and TensorFlowWho this book is for This book is ideal for data analysts, data scientists, and Python developers who want instantly useful and practical recipes to implement today, and a comprehensive reference book for tomorrow. Basic knowledge of the Python Programming language is a must, while familiarity with statistics will help you get the most out of this book.

Download or read book Machine Learning with PyTorch and Scikit Learn written by Sebastian Raschka and published by Packt Publishing Ltd. This book was released on 2022-02-25 with total page 775 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch s simple to code framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself. Why PyTorch? PyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP). This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.

Download or read book Eloquent Ruby written by Russ Olsen and published by Addison-Wesley Professional. This book was released on 2011-02-07 with total page 446 pages. Available in PDF, EPUB and Kindle. Book excerpt: It’s easy to write correct Ruby code, but to gain the fluency needed to write great Ruby code, you must go beyond syntax and absorb the “Ruby way” of thinking and problem solving. In Eloquent Ruby, Russ Olsen helps you write Ruby like true Rubyists do–so you can leverage its immense, surprising power. Olsen draws on years of experience internalizing the Ruby culture and teaching Ruby to other programmers. He guides you to the “Ah Ha!” moments when it suddenly becomes clear why Ruby works the way it does, and how you can take advantage of this language’s elegance and expressiveness. Eloquent Ruby starts small, answering tactical questions focused on a single statement, method, test, or bug. You’ll learn how to write code that actually looks like Ruby (not Java or C#); why Ruby has so many control structures; how to use strings, expressions, and symbols; and what dynamic typing is really good for. Next, the book addresses bigger questions related to building methods and classes. You’ll discover why Ruby classes contain so many tiny methods, when to use operator overloading, and when to avoid it. Olsen explains how to write Ruby code that writes its own code–and why you’ll want to. He concludes with powerful project-level features and techniques ranging from gems to Domain Specific Languages. A part of the renowned Addison-Wesley Professional Ruby Series, Eloquent Ruby will help you “put on your Ruby-colored glasses” and get results that make you a true believer.

Download or read book Realizing the Abidjan Principles on the Right to Education written by Frank Adamson and published by Edward Elgar Publishing. This book was released on 2021-05-28 with total page 296 pages. Available in PDF, EPUB and Kindle. Book excerpt: This insightful book analyses the process of the first adoption of guiding human rights principles for education, the Abidjan Principles. It explains the development of the Abidjan Principles, including their articulation of the right to education, the state obligation to provide quality public education, and the role of private actors in education.

Download or read book Test Driven Infrastructure with Chef written by Stephen Nelson-Smith and published by "O'Reilly Media, Inc.". This book was released on 2011-06-13 with total page 89 pages. Available in PDF, EPUB and Kindle. Book excerpt: Test-Driven Infrastructure with Chef demonstrates a radical approach to developing web infrastructure that combines the powerful Chef configuration management framework with Cucumber, the leading Behavior-driven development (BDD) tool. Learn how to deliver real business value by developing infrastructure code test-first. Infrastructure consultant Stephen Nelson-Smith shows you how this unique approach allows you to make significant changes without the fear of unexpected side effects—a great benefit when you’re developing code to control your production infrastructures. By using the test-first approach introduced in this book, you gain increased security, code quality, and peace of mind. Learn the core principles behind the infrastructure-as-code approach, including modularity, cooperation, extensibility, and flexibility Take a high-level tour of the Chef framework, tool, and API, as well as the community behind the project Set up a workstation to interact with the Chef API Get an overview of Cucumber and learn the principles of BDD Start using Cucumber-Chef, the open source infrastructure testing platform Explore test-driven infrastructure development with a hands-on tutorial

Download or read book The Practice of System and Network Administration written by Thomas A. Limoncelli and published by Addison-Wesley Professional. This book was released on 2016-10-25 with total page 1567 pages. Available in PDF, EPUB and Kindle. Book excerpt: With 28 new chapters, the third edition of The Practice of System and Network Administration innovates yet again! Revised with thousands of updates and clarifications based on reader feedback, this new edition also incorporates DevOps strategies even for non-DevOps environments. Whether you use Linux, Unix, or Windows, this new edition describes the essential practices previously handed down only from mentor to protégé. This wonderfully lucid, often funny cornucopia of information introduces beginners to advanced frameworks valuable for their entire career, yet is structured to help even experts through difficult projects. Other books tell you what commands to type. This book teaches you the cross-platform strategies that are timeless! DevOps techniques: Apply DevOps principles to enterprise IT infrastructure, even in environments without developers Game-changing strategies: New ways to deliver results faster with less stress Fleet management: A comprehensive guide to managing your fleet of desktops, laptops, servers and mobile devices Service management: How to design, launch, upgrade and migrate services Measurable improvement: Assess your operational effectiveness; a forty-page, pain-free assessment system you can start using today to raise the quality of all services Design guides: Best practices for networks, data centers, email, storage, monitoring, backups and more Management skills: Organization design, communication, negotiation, ethics, hiring and firing, and more Have you ever had any of these problems? Have you been surprised to discover your backup tapes are blank? Ever spent a year launching a new service only to be told the users hate it? Do you have more incoming support requests than you can handle? Do you spend more time fixing problems than building the next awesome thing? Have you suffered from a botched migration of thousands of users to a new service? Does your company rely on a computer that, if it died, can’t be rebuilt? Is your network a fragile mess that breaks any time you try to improve it? Is there a periodic “hell month” that happens twice a year? Twelve times a year? Do you find out about problems when your users call you to complain? Does your corporate “Change Review Board” terrify you? Does each division of your company have their own broken way of doing things? Do you fear that automation will replace you, or break more than it fixes? Are you underpaid and overworked? No vague “management speak” or empty platitudes. This comprehensive guide provides real solutions that prevent these problems and more!

Download or read book The Textual Warehouse written by Bill Inmon and published by . This book was released on 2021-07-12 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a Textual Warehouse to help your organization understand and analyze documents through text analytics (both sentiment and non-sentiment analysis), to make better business decisions. Learn the important role of documents and text within your organization, the difference between identifying and qualifying text, and when you need document preprocessing. Appreciate the power of taxonomies and the necessity of textual ETL. Know how the textual warehouse architecture differs from the conventional data warehouse architecture and when to apply contextualization and textual disambiguation. About Bill Bill Inmon, the "father of the data warehouse," has written 60 books published in nine languages. ComputerWorld named Bill one of the ten most influential people in the history of the computer profession. Bill's latest adventure is the building of technology known as textual disambiguation. About Ranjeet Ranjeet Srivastava is a data management professional and an enterprise architect with more than 20 years in enterprise product research, development, and design of data-intensive mission-critical applications.

Download or read book Deep Learning in Natural Language Processing written by Li Deng and published by Springer. This book was released on 2018-05-23 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, deep learning has fundamentally changed the landscapes of a number of areas in artificial intelligence, including speech, vision, natural language, robotics, and game playing. In particular, the striking success of deep learning in a wide variety of natural language processing (NLP) applications has served as a benchmark for the advances in one of the most important tasks in artificial intelligence. This book reviews the state of the art of deep learning research and its successful applications to major NLP tasks, including speech recognition and understanding, dialogue systems, lexical analysis, parsing, knowledge graphs, machine translation, question answering, sentiment analysis, social computing, and natural language generation from images. Outlining and analyzing various research frontiers of NLP in the deep learning era, it features self-contained, comprehensive chapters written by leading researchers in the field. A glossary of technical terms and commonly used acronyms in the intersection of deep learning and NLP is also provided. The book appeals to advanced undergraduate and graduate students, post-doctoral researchers, lecturers and industrial researchers, as well as anyone interested in deep learning and natural language processing.

Download or read book Refactoring written by Jay Fields and published by Pearson Education. This book was released on 2009-10-15 with total page 555 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Definitive Refactoring Guide, Fully Revamped for Ruby With refactoring, programmers can transform even the most chaotic software into well-designed systems that are far easier to evolve and maintain. What’s more, they can do it one step at a time, through a series of simple, proven steps. Now, there’s an authoritative and extensively updated version of Martin Fowler’s classic refactoring book that utilizes Ruby examples and idioms throughout–not code adapted from Java or any other environment. The authors introduce a detailed catalog of more than 70 proven Ruby refactorings, with specific guidance on when to apply each of them, step-by-step instructions for using them, and example code illustrating how they work. Many of the authors’ refactorings use powerful Ruby-specific features, and all code samples are available for download. Leveraging Fowler’s original concepts, the authors show how to perform refactoring in a controlled, efficient, incremental manner, so you methodically improve your code’s structure without introducing new bugs. Whatever your role in writing or maintaining Ruby code, this book will be an indispensable resource. This book will help you Understand the core principles of refactoring and the reasons for doing it Recognize “bad smells” in your Ruby code Rework bad designs into well-designed code, one step at a time Build tests to make sure your refactorings work properly Understand the challenges of refactoring and how they can be overcome Compose methods to package code properly Move features between objects to place responsibilities where they fit best Organize data to make it easier to work with Simplify conditional expressions and make more effective use of polymorphism Create interfaces that are easier to understand and use Generalize more effectively Perform larger refactorings that transform entire software systems and may take months or years Successfully refactor Ruby on Rails code

Download or read book Working Effectively with Legacy Code written by Michael Feathers and published by Prentice Hall Professional. This book was released on 2004-09-22 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get more out of your legacy systems: more performance, functionality, reliability, and manageability Is your code easy to change? Can you get nearly instantaneous feedback when you do change it? Do you understand it? If the answer to any of these questions is no, you have legacy code, and it is draining time and money away from your development efforts. In this book, Michael Feathers offers start-to-finish strategies for working more effectively with large, untested legacy code bases. This book draws on material Michael created for his renowned Object Mentor seminars: techniques Michael has used in mentoring to help hundreds of developers, technical managers, and testers bring their legacy systems under control. The topics covered include Understanding the mechanics of software change: adding features, fixing bugs, improving design, optimizing performance Getting legacy code into a test harness Writing tests that protect you against introducing new problems Techniques that can be used with any language or platform—with examples in Java, C++, C, and C# Accurately identifying where code changes need to be made Coping with legacy systems that aren't object-oriented Handling applications that don't seem to have any structure This book also includes a catalog of twenty-four dependency-breaking techniques that help you work with program elements in isolation and make safer changes.

Download or read book Architects of Intelligence written by Martin Ford and published by Packt Publishing Ltd. This book was released on 2018-11-23 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Financial Times Best Books of the Year 2018 TechRepublic Top Books Every Techie Should Read Book Description How will AI evolve and what major innovations are on the horizon? What will its impact be on the job market, economy, and society? What is the path toward human-level machine intelligence? What should we be concerned about as artificial intelligence advances? Architects of Intelligence contains a series of in-depth, one-to-one interviews where New York Times bestselling author, Martin Ford, uncovers the truth behind these questions from some of the brightest minds in the Artificial Intelligence community. Martin has wide-ranging conversations with twenty-three of the world's foremost researchers and entrepreneurs working in AI and robotics: Demis Hassabis (DeepMind), Ray Kurzweil (Google), Geoffrey Hinton (Univ. of Toronto and Google), Rodney Brooks (Rethink Robotics), Yann LeCun (Facebook) , Fei-Fei Li (Stanford and Google), Yoshua Bengio (Univ. of Montreal), Andrew Ng (AI Fund), Daphne Koller (Stanford), Stuart Russell (UC Berkeley), Nick Bostrom (Univ. of Oxford), Barbara Grosz (Harvard), David Ferrucci (Elemental Cognition), James Manyika (McKinsey), Judea Pearl (UCLA), Josh Tenenbaum (MIT), Rana el Kaliouby (Affectiva), Daniela Rus (MIT), Jeff Dean (Google), Cynthia Breazeal (MIT), Oren Etzioni (Allen Institute for AI), Gary Marcus (NYU), and Bryan Johnson (Kernel). Martin Ford is a prominent futurist, and author of Financial Times Business Book of the Year, Rise of the Robots. He speaks at conferences and companies around the world on what AI and automation might mean for the future. Meet the minds behind the AI superpowers as they discuss the science, business and ethics of modern artificial intelligence. Read James Manyika’s thoughts on AI analytics, Geoffrey Hinton’s breakthroughs in AI programming and development, and Rana el Kaliouby’s insights into AI marketing. This AI book collects the opinions of the luminaries of the AI business, such as Stuart Russell (coauthor of the leading AI textbook), Rodney Brooks (a leader in AI robotics), Demis Hassabis (chess prodigy and mind behind AlphaGo), and Yoshua Bengio (leader in deep learning) to complete your AI education and give you an AI advantage in 2019 and the future.

Download or read book Fifty Quick Ideas to Improve Your User Stories written by Gojko Adzic and published by Neuri Consulting Llp. This book was released on 2014-10-15 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book will help you write better stories, spot and fix common issues, split stories so that they are smaller but still valuable, and deal with difficult stuff like crosscutting concerns, long-term effects and non-functional requirements. Above all, this book will help you achieve the promise of agile and iterative delivery: to ensure that the right stuff gets delivered through productive discussions between delivery team members and business stakeholders. Who is this book for? This is a book for anyone working in an iterative delivery environment, doing planning with user stories. The ideas in this book are useful both to people relatively new to user stories and those who have been working with them for years. People who work in software delivery, regardless of their role, will find plenty of tips for engaging stakeholders better and structuring iterative plans more effectively. Business stakeholders working with software teams will discover how to provide better information to their delivery groups, how to set better priorities and how to outrun the competition by achieving more with less software. What's inside? Unsurprisingly, the book contains exactly fifty ideas. They are grouped into five major parts: - Creating stories: This part deals with capturing information about stories before they get accepted into the delivery pipeline. You'll find ideas about what kind of information to note down on story cards and how to quickly spot potential problems. - Planning with stories: This part contains ideas that will help you manage the big-picture view, set milestones and organise long-term work. - Discussing stories: User stories are all about effective conversations, and this part contains ideas to improve discussions between delivery teams and business stakeholders. You'll find out how to discover hidden assumptions and how to facilitate effective conversations to ensure shared understanding. - Splitting stories: The ideas in this part will help you deal with large and difficult stories, offering several strategies for dividing them into smaller chunks that will help you learn fast and deliver value quickly. - Managing iterative delivery: This part contains ideas that will help you work with user stories in the short and mid term, manage capacity, prioritise and reduce scope to achieve the most with the least software. About the authors: Gojko Adzic is a strategic software delivery consultant who works with ambitious teams to improve the quality of their software products and processes. Gojko's book Specification by Example was awarded the #2 spot on the top 100 agile books for 2012 and won the Jolt Award for the best book of 2012. In 2011, he was voted by peers as the most influential agile testing professional, and his blog won the UK agile award for the best online publication in 2010. David Evans is a consultant, coach and trainer specialising in the field of Agile Quality. David helps organisations with strategic process improvement and coaches teams on effective agile practice. He is regularly in demand as a conference speaker and has had several articles published in international journals.

Download or read book OpenSpace Beta written by Silke Hermann and published by Betacodex Publishing. This book was released on 2018-09-20 with total page 148 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook on the new and powerful OpenSpace Beta approach outlines how to "transform" your organization from Alpha to Beta in no more than a few months. With a foreword by Daniel Mezick, and an introduction to OpenSpace Technology by Harrison Owen.

Download or read book Data Science on AWS written by Chris Fregly and published by "O'Reilly Media, Inc.". This book was released on 2021-04-07 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: With this practical book, AI and machine learning practitioners will learn how to successfully build and deploy data science projects on Amazon Web Services. The Amazon AI and machine learning stack unifies data science, data engineering, and application development to help level upyour skills. This guide shows you how to build and run pipelines in the cloud, then integrate the results into applications in minutes instead of days. Throughout the book, authors Chris Fregly and Antje Barth demonstrate how to reduce cost and improve performance. Apply the Amazon AI and ML stack to real-world use cases for natural language processing, computer vision, fraud detection, conversational devices, and more Use automated machine learning to implement a specific subset of use cases with SageMaker Autopilot Dive deep into the complete model development lifecycle for a BERT-based NLP use case including data ingestion, analysis, model training, and deployment Tie everything together into a repeatable machine learning operations pipeline Explore real-time ML, anomaly detection, and streaming analytics on data streams with Amazon Kinesis and Managed Streaming for Apache Kafka Learn security best practices for data science projects and workflows including identity and access management, authentication, authorization, and more