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Floodplains are ecosystems which are driven by periodic inundation and oscillation between terrestrial and aquatic phases. An understanding of such pulsing systems is only possible by studying both phases and linking the results into an integrated overview. This book presents the results of a 15-year study of the structure and function of one of the largest tropical floodplains, the Amazon River floodplain. It covers qualitative aspects, e.g., adaptations of aquatic and terrestrial organisms to the flood pulse as well as quantitative aspects, e.g., studies of biomass, primary production, decomposition, and nutrient cycles. The authors interpret their findings and the most important data from other studies under an integrating scientific concept, the Flood Pulse Concept.

Amazon examines the world's largest online retailer, detailing its founding by Jeff Bezos and its expansion into new areas such as hardware devices, cloud services, and drone deliveries. Features include a glossary, references, websites, source notes, and an index. Aligned to Common Core Standards and correlated to state standards. Essential Library is an imprint of Abdo Publishing, a division of ABDO.

Amazon is the worldÕs largest online retailer! In this title, fluent readers will learn how it went from a bookstore based in a garage to one of the most recognizable brands in the world. Fact-filled text engages readers as they learn about AmazonÕs history, philanthropy, products, and more. Fun facts offer additional information, and special features map the companyÕs headquarters, highlight sales, profile a company leader, and show off popular products. This fun title delivers an informative and engaging read!

Swiftly build and deploy machine learning models without managing infrastructure and boost productivity using the latest Amazon SageMaker capabilities such as Studio, Autopilot, Data Wrangler, Pipelines, and Feature Store Key FeaturesBuild, train, and deploy machine learning models quickly using Amazon SageMakerOptimize the accuracy, cost, and fairness of your modelsCreate and automate end-to-end machine learning workflows on Amazon Web Services (AWS)Book Description Amazon SageMaker enables you to quickly build, train, and deploy machine learning models at scale without managing any infrastructure. It helps you focus on the machine learning problem at hand and deploy high-quality models by eliminating the heavy lifting typically involved in each step of the ML process. This second edition will help data scientists and ML developers to explore new features such as SageMaker Data Wrangler, Pipelines, Clarify, Feature Store, and much more. You'll start by learning how to use various capabilities of SageMaker as a single toolset to solve ML challenges and progress to cover features such as AutoML, built-in algorithms and frameworks, and writing your own code and algorithms to build ML models. The book will then show you how to integrate Amazon SageMaker with popular deep learning libraries, such as TensorFlow and PyTorch, to extend the capabilities of existing models. You'll also see how automating your workflows can help you get to production faster with minimum effort and at a lower cost. Finally, you'll explore SageMaker Debugger and SageMaker Model Monitor to detect quality issues in training and production. 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 learnBecome 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 natural language processing (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. A solid understanding of machine learning concepts and the Python programming language will also be beneficial.

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Amazon Web Services (AWS) provides on-demand cloud computing platforms and application programming interfaces (APIs) to individuals, companies, and govern- ments, along with distributed computing processing capacity and software tools via AWS server farms. This text presents a hands-on approach for beginners to get started with Amazon Web Services (AWS) in a simple way. Key Features It discusses topics such as Amazon Elastic Compute Cloud, Elastic Load Balancing, Auto Scaling Groups, and Amazon Simple Storage Service. It showcases Amazon Web Services’ identity, access management resources, and attribute-based access control. It covers serverless computing services, Virtual Private Cloud, Amazon Aurora, and Amazon Comprehend. It explains Amazon Web Services Free Tier, Amazon Web Services Marketplace, and Amazon Elastic Container Service. It includes security in Amazon Web Services, the shared responsibilitymodel, and high-performance computing on Amazon Web Services. The text is primarily written for graduate students, professionals, and academic researchers working in the fields of computer science, engineering, and information technology. Parul Dubey is currently working as an Assistant professor in the Department of Artificial Intelligence at G H Raisoni College of Engineering, Nagpur, India. She has filed for 15 Indian patents. She is responsible for about 10 publications in conference proceedings, Scopus, and journals. She has contributed book chapters in an edited book published by CRC Press and other reputed publishers. She is also an AWS Certified Cloud Practitioner. Rohit Raja is working as an associate professor and head in the Department of Information Technology at Guru Ghasidas Vishwavidyalaya, Bilaspur, India. His research interests include facial recognition, signal processing, networking, and data mining. He has pub- lished 100 research papers in various international and national journals (including publications by the IEEE, Springer, etc.) and proceedings of reputed international and national conferences (again including publications by Springer and the IEEE).

There is so much to explore in the Amazon! Readers are taken on an adventure through the Amazon rainforest to learn about the lush plants and beautiful animals, deforestation, and rainforest conservation in this fascinating nonfiction reader that features striking photographs and riveting facts.