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Lessons From Amazonia
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Book Synopsis Lessons from Amazonia by : Richard O. Bierregaard
Download or read book Lessons from Amazonia written by Richard O. Bierregaard and published by Yale University Press. This book was released on 2001-12-11 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deforestation is occurring at an alarming rate in many parts of the world, causing destruction of natural habitat and fragmentation of what remains. Nowhere is this problem more pressing than in the Amazon rainforest, which is rapidly vanishing in the face of enormous pressure from humans to exploit it. This book presents the results of the longest-running and most comprehensive study of forest fragmentation ever undertaken, the Biological Dynamics of Forest Fragments Project (BDFFP) in central Amazonia, the only experimental study of tropical forest fragmentation in which baseline data are available before isolation from continuous forest took place.A joint project of Brazil’s National Institute for Research in Amazonia and the U.S. Smithsonian Institution, the BDFFP has investigated the many effects that habitat fragmentation has on plants, invertebrates, and vertebrates. The book provides an overview of the BDFFP, reports on its case studies, looks at forest ecology and tree genetics, and considers what issues are involved in establishing conservation and management guidelines.
Book Synopsis SuperTargeting Amazon Affiliate Marketing Course by :
Download or read book SuperTargeting Amazon Affiliate Marketing Course written by and published by Amazon Affiliate Marketing. This book was released on with total page 82 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Sustainable Development in Practice by : Virgílio M. Viana
Download or read book Sustainable Development in Practice written by Virgílio M. Viana and published by IIED. This book was released on 2010 with total page 62 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Effective Amazon Machine Learning by : Alexis Perrier
Download or read book Effective Amazon Machine Learning written by Alexis Perrier and published by Packt Publishing Ltd. This book was released on 2017-04-25 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to leverage Amazon's powerful platform for your predictive analytics needs About This Book Create great machine learning models that combine the power of algorithms with interactive tools without worrying about the underlying complexity Learn the What's next? of machine learning—machine learning on the cloud—with this unique guide Create web services that allow you to perform affordable and fast machine learning on the cloud Who This Book Is For This book is intended for data scientists and managers of predictive analytics projects; it will teach beginner- to advanced-level machine learning practitioners how to leverage Amazon Machine Learning and complement their existing Data Science toolbox. No substantive prior knowledge of Machine Learning, Data Science, statistics, or coding is required. What You Will Learn Learn how to use the Amazon Machine Learning service from scratch for predictive analytics Gain hands-on experience of key Data Science concepts Solve classic regression and classification problems Run projects programmatically via the command line and the Python SDK Leverage the Amazon Web Service ecosystem to access extended data sources Implement streaming and advanced projects In Detail Predictive analytics is a complex domain requiring coding skills, an understanding of the mathematical concepts underpinning machine learning algorithms, and the ability to create compelling data visualizations. Following AWS simplifying Machine learning, this book will help you bring predictive analytics projects to fruition in three easy steps: data preparation, model tuning, and model selection. This book will introduce you to the Amazon Machine Learning platform and will implement core data science concepts such as classification, regression, regularization, overfitting, model selection, and evaluation. Furthermore, you will learn to leverage the Amazon Web Service (AWS) ecosystem for extended access to data sources, implement realtime predictions, and run Amazon Machine Learning projects via the command line and the Python SDK. Towards the end of the book, you will also learn how to apply these services to other problems, such as text mining, and to more complex datasets. Style and approach This book will include use cases you can relate to. In a very practical manner, you will explore the various capabilities of Amazon Machine Learning services, allowing you to implementing them in your environment with consummate ease.
Book Synopsis Accelerate Deep Learning Workloads with Amazon SageMaker by : Vadim Dabravolski
Download or read book Accelerate Deep Learning Workloads with Amazon SageMaker written by Vadim Dabravolski and published by Packt Publishing Ltd. This book was released on 2022-10-28 with total page 278 pages. Available in PDF, EPUB and Kindle. Book excerpt: Plan and design model serving infrastructure to run and troubleshoot distributed deep learning training jobs for improved model performance. Key FeaturesExplore key Amazon SageMaker capabilities in the context of deep learningTrain and deploy deep learning models using SageMaker managed capabilities and optimize your deep learning workloadsCover in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMakerBook Description Over the past 10 years, deep learning has grown from being an academic research field to seeing wide-scale adoption across multiple industries. Deep learning models demonstrate excellent results on a wide range of practical tasks, underpinning emerging fields such as virtual assistants, autonomous driving, and robotics. In this book, you will learn about the practical aspects of designing, building, and optimizing deep learning workloads on Amazon SageMaker. The book also provides end-to-end implementation examples for popular deep-learning tasks, such as computer vision and natural language processing. You will begin by exploring key Amazon SageMaker capabilities in the context of deep learning. Then, you will explore in detail the theoretical and practical aspects of training and hosting your deep learning models on Amazon SageMaker. You will learn how to train and serve deep learning models using popular open-source frameworks and understand the hardware and software options available for you on Amazon SageMaker. The book also covers various optimizations technique to improve the performance and cost characteristics of your deep learning workloads. By the end of this book, you will be fluent in the software and hardware aspects of running deep learning workloads using Amazon SageMaker. What you will learnCover key capabilities of Amazon SageMaker relevant to deep learning workloadsOrganize SageMaker development environmentPrepare and manage datasets for deep learning trainingDesign, debug, and implement the efficient training of deep learning modelsDeploy, monitor, and optimize the serving of DL modelsWho this book is for This book is relevant for ML engineers who work on deep learning model development and training, and for Solutions Architects who design and optimize end-to-end deep learning workloads. It assumes familiarity with the Python ecosystem, principles of Machine Learning and Deep Learning, and basic knowledge of the AWS cloud.
Book Synopsis Serverless Machine Learning with Amazon Redshift ML by : Debu Panda
Download or read book Serverless Machine Learning with Amazon Redshift ML written by Debu Panda and published by Packt Publishing Ltd. This book was released on 2023-08-30 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Supercharge and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale Key Features Leverage supervised learning to build binary classification, multi-class classification, and regression models Learn to use unsupervised learning using the K-means clustering method Master the art of time series forecasting using Redshift ML Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionAmazon Redshift Serverless enables organizations to run petabyte-scale cloud data warehouses quickly and in a cost-effective way, enabling data science professionals to efficiently deploy cloud data warehouses and leverage easy-to-use tools to train models and run predictions. This practical guide will help developers and data professionals working with Amazon Redshift data warehouses to put their SQL knowledge to work for training and deploying machine learning models. The book begins by helping you to explore the inner workings of Redshift Serverless as well as the foundations of data analytics and types of data machine learning. With the help of step-by-step explanations of essential concepts and practical examples, you’ll then learn to build your own classification and regression models. As you advance, you’ll find out how to deploy various types of machine learning projects using familiar SQL code, before delving into Redshift ML. In the concluding chapters, you’ll discover best practices for implementing serverless architecture with Redshift. By the end of this book, you’ll be able to configure and deploy Amazon Redshift Serverless, train and deploy machine learning models using Amazon Redshift ML, and run inference queries at scale.What you will learn Utilize Redshift Serverless for data ingestion, data analysis, and machine learning Create supervised and unsupervised models and learn how to supply your own custom parameters Discover how to use time series forecasting in your data warehouse Create a SageMaker endpoint and use that to build a Redshift ML model for remote inference Find out how to operationalize machine learning in your data warehouse Use model explainability and calculate probabilities with Amazon Redshift ML Who this book is forData scientists and machine learning developers working with Amazon Redshift who want to explore its machine-learning capabilities will find this definitive guide helpful. A basic understanding of machine learning techniques and working knowledge of Amazon Redshift is needed to make the most of this book.
Book Synopsis Machine Learning with Amazon SageMaker Cookbook by : Joshua Arvin Lat
Download or read book Machine Learning with Amazon SageMaker Cookbook written by Joshua Arvin Lat and published by Packt Publishing Ltd. This book was released on 2021-10-29 with total page 763 pages. Available in PDF, EPUB and Kindle. Book excerpt: A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key FeaturesPerform ML experiments with built-in and custom algorithms in SageMakerExplore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learnUse the different features and capabilities of SageMaker to automate relevant ML processesBook Description Amazon SageMaker is a fully managed machine learning (ML) service that helps data scientists and ML practitioners manage ML experiments. In this book, you'll use the different capabilities and features of Amazon SageMaker to solve relevant data science and ML problems. This step-by-step guide features 80 proven recipes designed to give you the hands-on machine learning experience needed to contribute to real-world experiments and projects. You'll cover the algorithms and techniques that are commonly used when training and deploying NLP, time series forecasting, and computer vision models to solve ML problems. You'll explore various solutions for working with deep learning libraries and frameworks such as TensorFlow, PyTorch, and Hugging Face Transformers in Amazon SageMaker. You'll also learn how to use SageMaker Clarify, SageMaker Model Monitor, SageMaker Debugger, and SageMaker Experiments to debug, manage, and monitor multiple ML experiments and deployments. Moreover, you'll have a better understanding of how SageMaker Feature Store, Autopilot, and Pipelines can meet the specific needs of data science teams. By the end of this book, you'll be able to combine the different solutions you've learned as building blocks to solve real-world ML problems. What you will learnTrain and deploy NLP, time series forecasting, and computer vision models to solve different business problemsPush the limits of customization in SageMaker using custom container imagesUse AutoML capabilities with SageMaker Autopilot to create high-quality modelsWork with effective data analysis and preparation techniquesExplore solutions for debugging and managing ML experiments and deploymentsDeal with bias detection and ML explainability requirements using SageMaker ClarifyAutomate intermediate and complex deployments and workflows using a variety of solutionsWho this book is for This book is for developers, data scientists, and machine learning practitioners interested in using Amazon SageMaker to build, analyze, and deploy machine learning models with 80 step-by-step recipes. All you need is an AWS account to get things running. Prior knowledge of AWS, machine learning, and the Python programming language will help you to grasp the concepts covered in this book more effectively.
Book Synopsis ⬆️ Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Practice Tests Exams 138 Questions & Answers PDF by : Daniel Danielecki
Download or read book ⬆️ Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Practice Tests Exams 138 Questions & Answers PDF written by Daniel Danielecki and published by Daniel Danielecki. This book was released on 2024-01-19 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: ⌛️ Short and to the point; why should you buy the PDF with these Practice Tests Exams: 1. Always happy to answer your questions on Google Play Books and outside :) 2. Failed? Please submit a screenshot of your exam result and request a refund; we'll always accept it. 3. Learn about topics, such as: - Amazon Athena; - Amazon CloudWatch; - Amazon Comprehend; - Amazon Elastic Compute Cloud (Amazon EC2); - Amazon Elastic Map Reduce (Amazon EMR); - Amazon Kinesis; - Amazon SageMaker; - Amazon Simple Storage Service (Amazon S3); - Amazon Textract; - Amazon Transcribe; - Apache Parquet; - Apache Spark; - AWS Batch; - AWS Glue; - AWS Lambda; - Convolutional Neural Network (CNN); - K-means; - Linear Regression; - Logistic Regression; - Principal Component Analysis (PCA); - Recurrent Neural Network (RNN); - Virtual Private Clouds (VPC); - Much More! 4. Questions are similar to the actual exam, without duplications (like in other courses ;-)). 5. These tests are not an Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Exam Dump. Some people use brain dumps or exam dumps, but that's absurd, which we don't practice. 6. 138 unique questions.
Book Synopsis ⬆️ Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Practice Tests Exams 138 Questions & No Answers PDF by : Daniel Danielecki
Download or read book ⬆️ Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Practice Tests Exams 138 Questions & No Answers PDF written by Daniel Danielecki and published by Daniel Danielecki. This book was released on 2024-01-19 with total page 69 pages. Available in PDF, EPUB and Kindle. Book excerpt: ⚠️ IMPORTANT: This PDF is without correct answers marked; that way, you can print it out or solve it digitally before checking the correct answers. We also sell this PDF with answers marked; please check our Shop to find one. ⌛️ Short and to the point; why should you buy the PDF with these Practice Tests Exams: 1. Always happy to answer your questions on Google Play Books and outside :) 2. Failed? Please submit a screenshot of your exam result and request a refund; we'll always accept it. 3. Learn about topics, such as: - Amazon Athena; - Amazon CloudWatch; - Amazon Comprehend; - Amazon Elastic Compute Cloud (Amazon EC2); - Amazon Elastic Map Reduce (Amazon EMR); - Amazon Kinesis; - Amazon SageMaker; - Amazon Simple Storage Service (Amazon S3); - Amazon Textract; - Amazon Transcribe; - Apache Parquet; - Apache Spark; - AWS Batch; - AWS Glue; - AWS Lambda; - Convolutional Neural Network (CNN); - K-means; - Linear Regression; - Logistic Regression; - Principal Component Analysis (PCA); - Recurrent Neural Network (RNN); - Virtual Private Clouds (VPC); - Much More! 4. Questions are similar to the actual exam, without duplications (like in other courses ;-)). 5. These tests are not an Amazon Web Services Certified (AWS Certified) Machine Learning Specialty (MLS-C01) Exam Dump. Some people use brain dumps or exam dumps, but that's absurd, which we don't practice. 6. 138 unique questions.
Book Synopsis AMAZON STOCK PRICE: VISUALIZATION, FORECASTING, AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI by : Vivian Siahaan
Download or read book AMAZON STOCK PRICE: VISUALIZATION, FORECASTING, AND PREDICTION USING MACHINE LEARNING WITH PYTHON GUI written by Vivian Siahaan and published by BALIGE PUBLISHING. This book was released on 2023-06-09 with total page 399 pages. Available in PDF, EPUB and Kindle. Book excerpt: Amazon is an American multinational technology company that is known for its e-commerce, cloud computing, digital streaming, and artificial intelligence services. It was founded by Jeff Bezos in 1994 and is headquartered in Seattle, Washington. Amazon's primary business is its online marketplace, where it offers a wide range of products, including books, electronics, household items, and more. The company has expanded its operations to various countries and is one of the largest online retailers globally. In addition to its e-commerce business, Amazon has ventured into other areas. It provides cloud computing services through Amazon Web Services (AWS), which offers on-demand computing power, storage, and other services to individuals, businesses, and governments. AWS has become a significant revenue source for Amazon. Amazon has also made a significant impact on the entertainment industry. It operates Amazon Prime Video, a streaming platform that offers a wide selection of movies, TV shows, and original content. As for Amazon's stock price, it has experienced substantial growth since the company went public in 1997. The stock has been highly valued by investors due to Amazon's consistent revenue growth, market dominance, and innovation. The stock price has seen both ups and downs over the years, reflecting market trends and investor sentiment. The dataset used in this project starts from 14-May-1997 and is updated till 27-Oct-2021. It contains 6155 rows and 7 columns. The columns in the dataset are Date, Open, High, Low, Close, Adj Close, and Volume. In this project, you will involve technical indicators such as daily returns, Moving Average Convergence-Divergence (MACD), Relative Strength Index (RSI), Simple Moving Average (SMA), lower and upper bands, and standard deviation. To perform forecasting based on regression on Adj Close price of Amazon stock price, you will use: Linear Regression, Random Forest regression, Decision Tree regression, Support Vector Machine regression, Naïve Bayes regression, K-Nearest Neighbor regression, Adaboost regression, Gradient Boosting regression, Extreme Gradient Boosting regression, Light Gradient Boosting regression, Catboost regression, MLP regression, Lasso regression, and Ridge regression. The machine learning models used predict Amazon stock daily returns as target variable are K-Nearest Neighbor classifier, Random Forest classifier, Naive Bayes classifier, Logistic Regression classifier, Decision Tree classifier, Support Vector Machine classifier, LGBM classifier, Gradient Boosting classifier, XGB classifier, MLP classifier, and Extra Trees classifier. Finally, you will develop GUI to plot boundary decision, distribution of features, feature importance, predicted values versus true values, confusion matrix, learning curve, performance of the model, and scalability of the model.
Book Synopsis Amazonia and Global Change by : Michael Keller
Download or read book Amazonia and Global Change written by Michael Keller and published by American Geophysical Union. This book was released on 2009-01-12 with total page 584 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published by the American Geophysical Union as part of the Geophysical Monograph Series, Volume 186. Amazonia and Global Change synthesizes results of the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) for scientists and students of Earth system science and global environmental change. LBA, led by Brazil, asks how Amazonia currently functions in the global climate and biogeochemical systems and how the functioning of Amazonia will respond to the combined pressures of climate and land use change, such as Wet season and dry season aerosol concentrations and their effects on diffuse radiation and photosynthesis Increasing greenhouse gas concentration, deforestation, widespread biomass burning and changes in the Amazonian water cycle Drought effects and simulated drought through rainfall exclusion experiments The net flux of carbon between Amazonia and the atmosphere Floodplains as an important regulator of the basin carbon balance including serving as a major source of methane to the troposphere The impact of the likely increased profitability of cattle ranching. The book will serve a broad community of scientists and policy makers interested in global change and environmental issues with high-quality scientific syntheses accessible to nonspecialists in a wide community of social scientists, ecologists, atmospheric chemists, climatologists, and hydrologists.
Book Synopsis Political Sociology of Adult Education by : Carlos Alberto Torres
Download or read book Political Sociology of Adult Education written by Carlos Alberto Torres and published by Springer Science & Business Media. This book was released on 2013-09-03 with total page 106 pages. Available in PDF, EPUB and Kindle. Book excerpt: Critical Theorist Carlos Alberto Torres offers a political sociology of adult learning and education, based on Critical Social Theory and the always inspiring work of Paulo Freire. Empirically grounded and theoretically sophisticated, this new book follows the footsteps of his classic book published in the early nineties The Politics of Nonformal Education in Latin America. Torres book offers comparative and international sociological analyses of adult learning and education, an area in which there is an obsession with ‘practice’ and an aversion to theory, with some notable and laudable exceptions, but which has the potential to provide avenues for social justice education in ways that no other systems and policies can. This book revitalizes social theory in education, and provides ample evidence of the power of adult learning and education, examining a variety of policy documents connected with the various adult education congresses promoted by the UNESCO, which are thoroughly scrutinized for what they bring to or omit from the policy agenda. In the context of new developments in adult learning and education, particularly the impact of multiple globalizations, neoliberalism, and the new role of international organizations in reconceptualizing lifelong learning, new evidence-based research, new narratives, and the vibrancy of social movements striving for a new and possible world, it is clear that new theoretical designs were needed making this is a must-read book.
Book Synopsis Biodiversity in the Brazilian Amazon by : João Paulo Ribeiro Capobianco
Download or read book Biodiversity in the Brazilian Amazon written by João Paulo Ribeiro Capobianco and published by . This book was released on 2004 with total page 550 pages. Available in PDF, EPUB and Kindle. Book excerpt: A situação socioambiental da Amazônia brasileira na virada do milênio. Resultado do esforço coletivo de cientistas, técnicos de órgãos públicos e de organizações não governamentais e lideranças do movimento social, esta obra traz 27 artigos de 47 autores, mais de uma centena de mapas temáticos, extensos bancos de dados e fotos de cinco renomados fotógrafos.
Book Synopsis A class-book of physical geography by : William Hughes
Download or read book A class-book of physical geography written by William Hughes and published by . This book was released on 1882 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis A Narrative of Travels on the Amazon and Rio Negro by : Alfred Russel Wallace
Download or read book A Narrative of Travels on the Amazon and Rio Negro written by Alfred Russel Wallace and published by . This book was released on 1889 with total page 424 pages. Available in PDF, EPUB and Kindle. Book excerpt: A Narrative of Travels on the Amazon and Rio Negro : With an Account of the Native Tribes, And Observations on the Climate, Geology, And Natural History of the Amazon Valley by Alfred Russel Wallace, first published in 1889, is a rare manuscript, the original residing in one of the great libraries of the world. This book is a reproduction of that original, which has been scanned and cleaned by state-of-the-art publishing tools for better readability and enhanced appreciation. Restoration Editors' mission is to bring long out of print manuscripts back to life. Some smudges, annotations or unclear text may still exist, due to permanent damage to the original work. We believe the literary significance of the text justifies offering this reproduction, allowing a new generation to appreciate it.
Book Synopsis Ecological Disorder and Amazonia by : International Social Science Council
Download or read book Ecological Disorder and Amazonia written by International Social Science Council and published by . This book was released on 1991 with total page 328 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Lessons of the Rainforest by : Suzanne Head
Download or read book Lessons of the Rainforest written by Suzanne Head and published by Random House (NY). This book was released on 1990 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: Essays from 24 leading authorities committed to finding alternatives to rain forest decimation.
