Exploring the Amazon
| Author | : Helen Schreider |
| Publisher | : |
| Total Pages | : 214 |
| Release | : 1970 |
| Genre | : History |
| ISBN | : |
Authors journey the length of the Amazon River from its five-inch-wide source high in the Andes to the Atlantic Ocean.
Exploring The Amazon
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Exploring the Pentium Era
| Author | : Conrad Riker |
| Publisher | : Conrad Riker |
| Total Pages | : 239 |
| Release | : 101-01-01 |
| Genre | : Computers |
| ISBN | : |
Get ready to learn about the journey from the humble beginnings of the tech industry to modern-day internet marvels! Do you remember the early days of dial-up internet and how we all had to format our computers? Do you wonder what drove those bearded hackers in Silicon Valley to create the technologies that changed our lives forever? Are you tired of talking about the same old "geek culture" and want to dive deeper into the hidden stories behind it all? Well, look no further! "Exploring the Pentium Era: From Socket 4 to Web 2.0" is here to help you understand the true impact of the I.T. industry on our society and how it shaped the world as we know it today. Within its pages, you will find: - The story of I.B.M.'s evolution and how it shaped the entire industry. - A deep understanding of early processors, from the Intel 4004 to the mighty Pentium Pro. - How geek culture took over mainstream society and what lessons we can learn from it. - The step-by-step evolution of the internet, from B.B.S. to the ever-evolving Web 2.0. Don't miss out on this chance to learn from the experts and uncover the hidden stories behind the tech industry's rise to prominence. If you want to unlock the secrets of the past and see how they shaped the present, then is the book for you. Get your copy today and embark on an unforgettable journey through history!
Generative AI with Amazon Bedrock
| Author | : Shikhar Kwatra |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 384 |
| Release | : 2024-07-31 |
| Genre | : Computers |
| ISBN | : 1804618586 |
Become proficient in Amazon Bedrock by taking a hands-on approach to building and scaling generative AI solutions that are robust, secure, and compliant with ethical standards Key Features Learn the foundations of Amazon Bedrock from experienced AWS Machine Learning Specialist Architects Master the core techniques to develop and deploy several AI applications at scale Go beyond writing good prompting techniques and secure scalable frameworks by using advanced tips and tricks Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe concept of generative artificial intelligence has garnered widespread interest, with industries looking to leverage it to innovate and solve business problems. Amazon Bedrock, along with LangChain, simplifies the building and scaling of generative AI applications without needing to manage the infrastructure. Generative AI with Amazon Bedrock takes a practical approach to enabling you to accelerate the development and integration of several generative AI use cases in a seamless manner. You’ll explore techniques such as prompt engineering, retrieval augmentation, fine-tuning generative models, and orchestrating tasks using agents. The chapters take you through real-world scenarios and use cases such as text generation and summarization, image and code generation, and the creation of virtual assistants. The latter part of the book shows you how to effectively monitor and ensure security and privacy in Amazon Bedrock. By the end of this book, you’ll have gained a solid understanding of building and scaling generative AI apps using Amazon Bedrock, along with various architecture patterns and security best practices that will help you solve business problems and drive innovation in your organization.What you will learn Explore the generative AI landscape and foundation models in Amazon Bedrock Fine-tune generative models to improve their performance Explore several architecture patterns for different business use cases Gain insights into ethical AI practices, model governance, and risk mitigation strategies Enhance your skills in employing agents to develop intelligence and orchestrate tasks Monitor and understand metrics and Amazon Bedrock model response Explore various industrial use cases and architectures to solve real-world business problems using RAG Stay on top of architectural best practices and industry standards Who this book is for This book is for generalist application engineers, solution engineers and architects, technical managers, ML advocates, data engineers, and data scientists looking to either innovate within their organization or solve business use cases using generative AI. A basic understanding of AWS APIs and core AWS services for machine learning is expected.
AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide
| Author | : Somanath Nanda |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 343 |
| Release | : 2024-02-29 |
| Genre | : Computers |
| ISBN | : 1835082904 |
Prepare confidently for the AWS MLS-C01 certification with this comprehensive and up-to-date exam guide, accompanied by web-based tools such as mock exams, flashcards, and exam tips Key Features Gain proficiency in AWS machine learning services to excel in the MLS-C01 exam Build model training and inference pipelines and deploy machine learning models to the AWS cloud Practice on the go with the mobile-friendly bonus website, accessible with the book Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionThe AWS Certified Machine Learning Specialty (MLS-C01) exam evaluates your ability to execute machine learning tasks on AWS infrastructure. This comprehensive book aligns with the latest exam syllabus, offering practical examples to support your real-world machine learning projects on AWS. Additionally, you'll get lifetime access to supplementary online resources, including mock exams with exam-like timers, detailed solutions, interactive flashcards, and invaluable exam tips, all accessible across various devices—PCs, tablets, and smartphones. Throughout the book, you’ll learn data preparation techniques for machine learning, covering diverse methods for data manipulation and transformation across different variable types. Addressing challenges such as missing data and outliers, the book guides you through an array of machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, accompanied by requisite machine learning algorithms essential for exam success. The book helps you master the deployment of models in production environments and their subsequent monitoring. Equipped with insights from this book and the accompanying mock exams, you'll be fully prepared to achieve the AWS MLS-C01 certification.What you will learn Identify ML frameworks for specific tasks Apply CRISP-DM to build ML pipelines Combine AWS services to build AI/ML solutions Apply various techniques to transform your data, such as one-hot encoding, binary encoder, ordinal encoding, binning, and text transformations Visualize relationships, comparisons, compositions, and distributions in the data Use data preparation techniques and AWS services for batch and real-time data processing Create training and inference ML pipelines with Sage Maker Deploy ML models in a production environment efficiently Who this book is for This book is designed for both students and professionals preparing for the AWS Certified Machine Learning Specialty exam or enhance their understanding of machine learning, with a specific emphasis on AWS. Familiarity with machine learning basics and AWS services is recommended to fully benefit from this book.
Learn Amazon SageMaker
| Author | : Julien Simon |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 490 |
| Release | : 2020-08-27 |
| Genre | : Computers |
| ISBN | : 1800203594 |
Quickly build and deploy machine learning models without managing infrastructure, and improve productivity using Amazon SageMaker’s capabilities such as Amazon SageMaker Studio, Autopilot, Experiments, Debugger, and Model Monitor Key FeaturesBuild, train, and deploy machine learning models quickly using Amazon SageMakerAnalyze, detect, and receive alerts relating to various business problems using machine learning algorithms and techniquesImprove productivity by training and fine-tuning machine learning models in productionBook Description Amazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure. It helps you focus on the ML problem at hand and deploy high-quality models by removing the heavy lifting typically involved in each step of the ML process. This book is a comprehensive guide for data scientists and ML developers who want to learn the ins and outs of Amazon SageMaker. You’ll understand how to use various modules of SageMaker as a single toolset to solve the challenges faced in ML. As you progress, you’ll cover features such as AutoML, built-in algorithms and frameworks, and the option for writing your own code and algorithms to build ML models. Later, the book will show you how to integrate Amazon SageMaker with popular deep learning libraries such as TensorFlow and PyTorch to increase the capabilities of existing models. You’ll also learn to get the models to production faster with minimum effort and at a lower cost. Finally, you’ll explore how to use Amazon SageMaker Debugger to analyze, detect, and highlight problems to understand the current model state and improve model accuracy. By the end of this Amazon book, you’ll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation. What you will learnCreate and automate end-to-end machine learning workflows on Amazon Web Services (AWS)Become well-versed with data annotation and preparation techniquesUse AutoML features to build and train machine learning models with AutoPilotCreate models using built-in algorithms and frameworks and your own codeTrain computer vision and NLP models using real-world examplesCover training techniques for scaling, model optimization, model debugging, and cost optimizationAutomate deployment tasks in a variety of configurations using SDK and several automation toolsWho this book is for This book is for software engineers, machine learning developers, data scientists, and AWS users who are new to using Amazon SageMaker and want to build high-quality machine learning models without worrying about infrastructure. Knowledge of AWS basics is required to grasp the concepts covered in this book more effectively. Some understanding of machine learning concepts and the Python programming language will also be beneficial.
Journal of the American Geographical Society of New York
| Author | : American Geographical Society of New York |
| Publisher | : |
| Total Pages | : 836 |
| Release | : 1891 |
| Genre | : Electronic journals |
| ISBN | : |
Mastering Amazon Relational Database Service for MySQL
| Author | : Jeyaram Ayyalusamy |
| Publisher | : BPB Publications |
| Total Pages | : 564 |
| Release | : 2024-02-05 |
| Genre | : Computers |
| ISBN | : 9355519362 |
Toolkit for unlocking the power of Amazon RDS and propelling businesses toward success in the digital age KEY FEATURES ● Explore Amazon RDS by covering basics to advanced MySQL management on the platform. ● Real-world examples and hands-on tutorials to apply gained knowledge to solve challenges. ● Latest features, tools, and best practices in Amazon RDS for MySQL by covering recent developments. DESCRIPTION This book is a valuable resource as a practical guide for professionals involved in managing Amazon Relational Database Service (RDS) instances. The book covers the fundamentals of Amazon RDS, configuration best practices, and optimizing performance. With MySQL databases, it explores essential components, AWS Regions, and Availability Zones. Readers will benefit from the detailed discussions on managing and maintaining Amazon RDS MySQL instances, covering topics like stopping and starting DB instances, optimizing settings, handling maintenance updates, and understanding the nuances of reboots. The book emphasizes security considerations and provides a comprehensive guide to storage management, encryption options, backup strategies, and cost optimization. The later chapters delve into advanced topics such as creating and connecting to MySQL databases on Amazon RDS, managing Multi-AZ MySQL DB clusters, and upgrading AWS RDS MySQL. The book also covers comprehensive monitoring techniques, tools, and insights, offering a thorough exploration of CloudWatch metrics, alarms, and event notifications. Throughout the book, best practices, common issues, and troubleshooting tips are provided, making it an indispensable companion for database administrators navigating the complexities of Amazon RDS for MySQL. WHAT YOU WILL LEARN ● The fundamentals of Amazon RDS and how it simplifies the management of MySQL databases. ● How to set up, configure, and deploy MySQL instances on Amazon RDS. ● Best practices for designing highly available and scalable database architectures. ● Performance optimization techniques to ensure your MySQL databases run efficiently on Amazon RDS. ● Advanced topics such as replication, security, monitoring, and troubleshooting. WHO THIS BOOK IS FOR Whether you are a database administrator, a software developer, a system architect, or a technology enthusiast, this book provides valuable insights and practical guidance for effectively utilizing Amazon RDS. TABLE OF CONTENTS 1. Amazon Relational Database Service 2. Configuring a DB Instance for Amazon RDS MySQL 3. Managing and Maintaining an Amazon RDS MySQL Instance 4. Creating and Connecting to MySQL Database on Amazon RDS 5. Managing Amazon RDS Multi-AZ MySQL DB Clusters 6. Amazon RDS MySQL Backups: Best Practices for Data Integrity and Business Continuity 7. Upgrading AWS RDS MySQL 8. Comprehensive Amazon RDS MySQL Monitoring: Metrics, Tools, and Insights 9. Comprehensive Monitoring Tools for Amazon RDS and AWS Solutions 10. Understanding Amazon RDS Read Replicas: Scaling and High Availability
