Time Series Analysis On Aws
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Time Series Analysis On Aws
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Author : Michaël Hoarau
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-02-28
Time Series Analysis On Aws written by Michaël Hoarau and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-28 with Computers categories.
Leverage AWS AI/ML managed services to generate value from your time series data Key FeaturesSolve modern time series analysis problems such as forecasting and anomaly detectionGain a solid understanding of AWS AI/ML managed services and apply them to your business problemsExplore different algorithms to build applications that leverage time series dataBook Description Being a business analyst and data scientist, you have to use many algorithms and approaches to prepare, process, and build ML-based applications by leveraging time series data, but you face common problems, such as not knowing which algorithm to choose or how to combine and interpret them. Amazon Web Services (AWS) provides numerous services to help you build applications fueled by artificial intelligence (AI) capabilities. This book helps you get to grips with three AWS AI/ML-managed services to enable you to deliver your desired business outcomes. The book begins with Amazon Forecast, where you'll discover how to use time series forecasting, leveraging sophisticated statistical and machine learning algorithms to deliver business outcomes accurately. You'll then learn to use Amazon Lookout for Equipment to build multivariate time series anomaly detection models geared toward industrial equipment and understand how it provides valuable insights to reinforce teams focused on predictive maintenance and predictive quality use cases. In the last chapters, you'll explore Amazon Lookout for Metrics, and automatically detect and diagnose outliers in your business and operational data. By the end of this AWS book, you'll have understood how to use the three AWS AI services effectively to perform time series analysis. What you will learnUnderstand how time series data differs from other types of dataExplore the key challenges that can be solved using time series dataForecast future values of business metrics using Amazon ForecastDetect anomalies and deliver forewarnings using Lookout for EquipmentDetect anomalies in business metrics using Amazon Lookout for MetricsVisualize your predictions to reduce the time to extract insightsWho this book is for If you're a data analyst, business analyst, or data scientist looking to analyze time series data effectively for solving business problems, this is the book for you. Basic statistics knowledge is assumed, but no machine learning knowledge is necessary. Prior experience with time series data and how it relates to various business problems will help you get the most out of this book. This guide will also help machine learning practitioners find new ways to leverage their skills to build effective time series-based applications.
Time Series Analysis With Python Cookbook
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Author : Tarek A. Atwan
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-06-30
Time Series Analysis With Python Cookbook written by Tarek A. Atwan and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-30 with Computers categories.
Perform time series analysis and forecasting confidently with this Python code bank and reference manual Key Features • Explore forecasting and anomaly detection techniques using statistical, machine learning, and deep learning algorithms • Learn different techniques for evaluating, diagnosing, and optimizing your models • Work with a variety of complex data with trends, multiple seasonal patterns, and irregularities Book Description Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting. This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you'll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, ACF and PACF plots, and decomposing time series data with multiple seasonal patterns. Later, you'll work with ML and DL models using TensorFlow and PyTorch. Finally, you'll learn how to evaluate, compare, optimize models, and more using the recipes covered in the book. What you will learn • Understand what makes time series data different from other data • Apply various imputation and interpolation strategies for missing data • Implement different models for univariate and multivariate time series • Use different deep learning libraries such as TensorFlow, Keras, and PyTorch • Plot interactive time series visualizations using hvPlot • Explore state-space models and the unobserved components model (UCM) • Detect anomalies using statistical and machine learning methods • Forecast complex time series with multiple seasonal patterns Who this book is for This book is for data analysts, business analysts, data scientists, data engineers, or Python developers who want practical Python recipes for time series analysis and forecasting techniques. Fundamental knowledge of Python programming is required. Although having a basic math and statistics background will be beneficial, it is not necessary. Prior experience working with time series data to solve business problems will also help you to better utilize and apply the different recipes in this book.
Implementing Mlops In The Enterprise
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Author : Yaron Haviv
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-30
Implementing Mlops In The Enterprise written by Yaron Haviv and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-30 with Computers categories.
With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Build production applications with LLMs and Generative AI, while reducing risks, increasing the efficiency, and fine tuning models Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy
Aws Timestream Data Management And Analysis
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-05-28
Aws Timestream Data Management And Analysis written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-28 with Computers categories.
"AWS Timestream Data Management and Analysis" Discover the definitive guide to harnessing the power of AWS Timestream with "AWS Timestream Data Management and Analysis." Designed for architects, engineers, and analytic professionals, this comprehensive book delves deeply into time series data concepts and the unique architectural foundations underpinning Timestream. It offers a clear exploration of how AWS Timestream compares to traditional RDBMS, NoSQL, and other time series solutions, highlighting its data structures, scalability strategies, and ideal deployment scenarios in the modern cloud. The book provides hands-on guidance for provisioning, configuring, and optimizing Timestream environments at every stage of the data lifecycle. Readers will gain practical insights into efficient data ingestion—batch, micro-batch, and streaming—as well as robust integration with AWS services like Kinesis, Lambda, QuickSight, and Glue. Detailed chapters address advanced data modeling, analytics, and storage optimization techniques, along with cost management, security best practices, compliance frameworks, and performance tuning. Each topic is presented through clear explanations and actionable patterns, empowering professionals to architect reliable, high-performance time series solutions for IoT, DevOps, financial, and manufacturing applications. Looking toward the future, the book explores emerging innovations such as serverless analytics, edge computing, AI/ML integrations, and zero-ETL architectures, while also surveying open standards and next-generation cloud strategies. Real-world case studies and industry applications illustrate Timestream’s value across diverse sectors, providing readers with practical blueprints for success. Whether you're building scalable telemetry pipelines, predictive analytics engines, or secure, multi-tenant data architectures, this authoritative guide offers the tools, context, and confidence to excel with AWS Timestream.
Deep Learning
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Author : Dr. C. Thangamani
language : en
Publisher: RK Publication
Release Date : 2024-10-28
Deep Learning written by Dr. C. Thangamani and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-28 with Computers categories.
Deep Learning is a artificial neural networks and their application to machine learning. The foundational concepts, techniques, and algorithms that drive deep learning, providing both theoretical insights and practical implementation strategies. It covers various architectures such as convolutional and recurrent networks, deep reinforcement learning, and unsupervised learning, while also addressing challenges like overfitting, model interpretability, and optimization. Suitable for both beginners and advanced learners, it offers a solid foundation in understanding and applying deep learning in real-world scenarios.
Monthly Weather Review
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Author :
language : en
Publisher:
Release Date : 1989
Monthly Weather Review written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1989 with Meteorology categories.
Aws Certified Machine Learning Study Guide
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Author : Shreyas Subramanian
language : en
Publisher: John Wiley & Sons
Release Date : 2021-11-19
Aws Certified Machine Learning Study Guide written by Shreyas Subramanian and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-19 with Computers categories.
Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions. The AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working within the AWS architecture. From exam to interview to your first day on the job, this study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud. And with the practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide, you’ll be prepared for success in every subject area covered by the exam. You’ll also find: An intuitive and organized layout perfect for anyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learning on the AWS Cloud Authoritative instruction on a widely recognized certification that unlocks countless career opportunities in machine learning and data science Access to the Sybex online learning resources and test bank, with chapter review questions, a full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam is an indispensable guide for anyone seeking to prepare themselves for success on the AWS Certified Machine Learning Specialty exam or for a job interview in the field of machine learning, or who wishes to improve their skills in the field as they pursue a career in AWS machine learning.
Solutions Architect S Handbook
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Author : Saurabh Shrivastava
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-01-17
Solutions Architect S Handbook written by Saurabh Shrivastava and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-17 with Computers categories.
Third edition out now with coverage on Generative AI, clean architecture, edge computing, and more Key Features Turn business needs into end-to-end technical architectures with this practical guide Assess and overcome various challenges while updating or modernizing legacy applications Future-proof your architecture with IoT, machine learning, and quantum computing Book DescriptionBecoming a solutions architect requires a hands-on approach, and this edition of the Solutions Architect's Handbook brings exactly that. This handbook will teach you how to create robust, scalable, and fault-tolerant solutions and next-generation architecture designs in a cloud environment. It will also help you build effective product strategies for your business and implement them from start to finish. This new edition features additional chapters on disruptive technologies, such as Internet of Things (IoT), quantum computing, data engineering, and machine learning. It also includes updated discussions on cloud-native architecture, blockchain data storage, and mainframe modernization with public cloud. The Solutions Architect's Handbook provides an understanding of solution architecture and how it fits into an agile enterprise environment. It will take you through the journey of solution architecture design by providing detailed knowledge of design pillars, advanced design patterns, anti-patterns, and the cloud-native aspects of modern software design. By the end of this handbook, you'll have learned the techniques needed to create efficient architecture designs that meet your business requirements.What you will learn Explore the various roles of a solutions architect in the enterprise landscape Implement key design principles and patterns to build high-performance cost-effective solutions Choose the best strategies to secure your architectures and increase their availability Modernize legacy applications with the help of cloud integration Understand how big data processing, machine learning, and IoT fit into modern architecture Integrate a DevOps mindset to promote collaboration, increase operational efficiency, and streamline production Who this book is for This book is for software developers, system engineers, DevOps engineers, architects, and team leaders who already work in the IT industry and aspire to become solutions architect professionals. Existing solutions architects who want to expand their skillset or get a better understanding of new technologies will also learn valuable new skills. To get started, you'll need a good understanding of the real-world software development process and general programming experience in any language.
Predictive Analytics For The Modern Enterprise
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Author : Nooruddin Abbas Ali
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-20
Predictive Analytics For The Modern Enterprise written by Nooruddin Abbas Ali and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-20 with Computers categories.
The surging predictive analytics market is expected to grow from $10.5 billion today to $28 billion by 2026. With the rise in automation across industries, the increase in data-driven decision-making, and the proliferation of IoT devices, predictive analytics has become an operational necessity in today's forward-thinking companies. If you're a data professional, you need to be aligned with your company's business activities more than ever before. This practical book provides the background, tools, and best practices necessary to help you design, implement, and operationalize predictive analytics on-premises or in the cloud. Explore ways that predictive analytics can provide direct input back to your business Understand mathematical tools commonly used in predictive analytics Learn the development frameworks used in predictive analytics applications Appreciate the role of predictive analytics in the machine learning process Examine industry implementations of predictive analytics Build, train, and retrain predictive models using Python and TensorFlow
Ai Fundamentals Courseware
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Author : Reinier van den Biggelaar
language : en
Publisher: Van Haren
Release Date : 2023-09-26
Ai Fundamentals Courseware written by Reinier van den Biggelaar and has been published by Van Haren this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-26 with Architecture categories.
The AI Fundamentals courseware offers an AI training course designed for professionals in business or government environments who want to understand the benefits and applications of AI in their work environment. This course covers topics such as data management for AI, building and assessing AI applications, ethics and trustworthiness, and organizational success factors for enabling humans and machines to work together. The course addresses key questions such as “Where does Data Management end and AI application begin?” from a management perspective. Subjects covered include the applications and benefits of AI, data and robots, predictions and algorithms, machine and deep learning, building and reviewing AI applications, data management for AI, ethics and trustworthiness, organizational success factors for helping humans and machines work together, and the future of AI. This courseware educates for three certifications within it’s three-day combined program. It’s also possible to cut the material in pieces for a module teaching approach. The EXIN BCS Artificial Intelligence Essentials, testing the fundamental concepts of AI. This AI for Business and Government certification (the AI Brevet) which was established by the Netherlands AI Coalition (NL AIC) as a standard for professionals who want to use Artificial Intelligence. EXIN BCS Artificial Intelligence Foundation, which has a more IT-technical perspective.