Effective Amazon Machine Learning

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Effective Amazon Machine Learning

Author : Alexis Perrier
Publisher : Packt Publishing Ltd
ISBN 13 : 1785881795
Total Pages : 298 pages
Book Rating : 4.7/5 (858 download)

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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.

Effective Amazon Machine Learning

Author : Alexis Perrier
Publisher : Packt Publishing Ltd
ISBN 13 : 1785881795
Total Pages : 298 pages
Book Rating : 4.7/5 (858 download)

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Book Synopsis Effective Amazon Machine Learning by : Alexis Perrier

AWS Certified AI & Machine Learning Specialist

Author :
Publisher : Cybellium
ISBN 13 : 1836798830
Total Pages : 230 pages
Book Rating : 4.8/5 (367 download)

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Book Synopsis AWS Certified AI & Machine Learning Specialist by :

Download or read book AWS Certified AI & Machine Learning Specialist written by and published by Cybellium . This book was released on with total page 230 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

AWS certification guide - AWS Certified Machine Learning - Specialty

Author :
Publisher : Cybellium Ltd
ISBN 13 :
Total Pages : 167 pages
Book Rating : 4.8/5 (712 download)

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Book Synopsis AWS certification guide - AWS Certified Machine Learning - Specialty by :

Download or read book AWS certification guide - AWS Certified Machine Learning - Specialty written by and published by Cybellium Ltd. This book was released on with total page 167 pages. Available in PDF, EPUB and Kindle. Book excerpt: AWS Certification Guide - AWS Certified Machine Learning – Specialty Unleash the Potential of AWS Machine Learning Embark on a comprehensive journey into the world of machine learning on AWS with this essential guide, tailored for those pursuing the AWS Certified Machine Learning – Specialty certification. This book is a valuable resource for professionals seeking to harness the power of AWS for machine learning applications. Inside, You'll Explore: Foundational to Advanced ML Concepts: Understand the breadth of AWS machine learning services and tools, from SageMaker to DeepLens, and learn how to apply them in various scenarios. Practical Machine Learning Scenarios: Delve into real-world examples and case studies, illustrating the practical applications of AWS machine learning technologies in different industries. Targeted Exam Preparation: Navigate the certification exam with confidence, thanks to detailed insights into the exam format, including specific chapters aligned with the certification objectives and comprehensive practice questions. Latest Trends and Best Practices: Stay at the forefront of machine learning advancements with up-to-date coverage of the latest AWS features and industry best practices. Written by a Machine Learning Expert Authored by an experienced practitioner in AWS machine learning, this guide combines in-depth knowledge with practical insights, providing a rich and comprehensive learning experience. Your Comprehensive Resource for ML Certification Whether you are deepening your existing machine learning skills or embarking on a new specialty in AWS, this book is your definitive companion, offering an in-depth exploration of AWS machine learning services and preparing you for the Specialty certification exam. Advance Your Machine Learning Career Beyond preparing for the exam, this guide is about mastering the complexities of AWS machine learning. It's a pathway to developing expertise that can be applied in innovative and transformative ways across various sectors. Start Your Specialized Journey in AWS Machine Learning Set off on your path to becoming an AWS Certified Machine Learning specialist. This guide is your first step towards mastering AWS machine learning and unlocking new opportunities in this exciting and rapidly evolving field. © 2023 Cybellium Ltd. All rights reserved. www.cybellium.com

Cloud Native AI and Machine Learning on AWS

Author : Premkumar Rangarajan
Publisher : BPB Publications
ISBN 13 : 9355513267
Total Pages : 366 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Cloud Native AI and Machine Learning on AWS by : Premkumar Rangarajan

Download or read book Cloud Native AI and Machine Learning on AWS written by Premkumar Rangarajan and published by BPB Publications. This book was released on 2023-02-14 with total page 366 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bring elasticity and innovation to Machine Learning and AI operations KEY FEATURES ● Coverage includes a wide range of AWS AI and ML services to help you speedily get fully operational with ML. ● Packed with real-world examples, practical guides, and expert data science methods for improving AI/ML education on AWS. ● Includes ready-made, purpose-built models as AI services and proven methods to adopt MLOps techniques. DESCRIPTION Using machine learning and artificial intelligence (AI) in existing business processes has been successful. Even AWS's ML and AI services make it simple and economical to conduct machine learning experiments. This book will show readers how to use the complete set of AI and ML services available on AWS to streamline the management of their whole AI operation and speed up their innovation. In this book, you'll learn how to build data lakes, build and train machine learning models, automate MLOps, ensure maximum data reusability and reproducibility, and much more. The applications presented in the book show how to make the most of several different AWS offerings, including Amazon Comprehend, Amazon Rekognition, Amazon Lookout, and AutoML. This book teaches you to manage massive data lakes, train artificial intelligence models, release these applications into production, and track their progress in real-time. You will learn how to use the pre-trained models for various tasks, including picture recognition, automated data extraction, image/video detection, and anomaly detection. Every step of your Machine Learning and AI project's development process is optimised throughout the book by utilising Amazon's pre-made, purpose-built AI services. WHAT YOU WILL LEARN ● Learn how to build, deploy, and manage large-scale AI and ML applications on AWS. ● Get your hands dirty with AWS AI services like SageMaker, Comprehend, Rekognition, Lookout, and AutoML. ● Master data transformation, feature engineering, and model training with Amazon SageMaker modules. ● Use neural networks, distributed learning, and deep learning algorithms to improve ML models. ● Use AutoML, SageMaker Canvas, and Autopilot for Model Deployment and Evaluation. ● Acquire expertise with Amazon SageMaker Studio, Jupyter Server, and ML frameworks such as TensorFlow and MXNet. WHO THIS BOOK IS FOR Data Engineers, Data Scientists, AWS and Cloud Professionals who are comfortable with machine learning and the fundamentals of Python will find this book powerful. Familiarity with AWS would be helpful but is not required. TABLE OF CONTENTS 1. Introducing the ML Workflow 2. Hydrating the Data Lake 3. Predicting the Future With Features 4. Orchestrating the Data Continuum 5. Casting a Deeper Net (Algorithms and Neural Networks) 6. Iteration Makes Intelligence (Model Training and Tuning) 7. Let George Take Over (AutoML in Action) 8. Blue or Green (Model Deployment Strategies) 9. Wisdom at Scale with Elastic Inference 10. Adding Intelligence with Sensory Cognition 11. AI for Industrial Automation 12. Operationalized Model Assembly (MLOps and Best Practices)

AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide

Author : Somanath Nanda
Publisher : Packt Publishing Ltd
ISBN 13 : 1835082904
Total Pages : 343 pages
Book Rating : 4.8/5 (35 download)

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Book Synopsis AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide by : Somanath Nanda

Download or read book AWS Certified Machine Learning - Specialty (MLS-C01) Certification Guide written by Somanath Nanda and published by Packt Publishing Ltd. This book was released on 2024-02-29 with total page 343 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs

Author : Peter Jones
Publisher : Walzone Press
ISBN 13 :
Total Pages : 153 pages
Book Rating : 4./5 ( download)

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Book Synopsis Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs by : Peter Jones

Download or read book Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs written by Peter Jones and published by Walzone Press. This book was released on 2024-10-13 with total page 153 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unlock the full potential of machine learning with "Machine Learning in the Cloud: Comparing Google Cloud, AWS, and Azure APIs." This essential guide meticulously navigates through the intricate world of cloud-based ML APIs across the leading platforms—Google Cloud, AWS, and Azure. Whether you're a software developer, data scientist, IT professional, or business strategist, this book equips you with the knowledge to make informed decisions about implementing and managing these powerful tools in your projects. Dive deep into a comprehensive analysis and comparison of text processing, image recognition, speech recognition, and custom model building services offered by these giants. Understand the ins and outs of setting up, configuring, and optimizing these APIs for performance and scalability. Explore chapters dedicated to security, compliance, and real-life success stories that demonstrate the transformative impact of cloud-based ML across various industries. With practical guides, strategic insights, and current industry standards, this book is your roadmap to mastering cloud machine learning APIs, paving the way for innovative solutions that enhance competitiveness and efficiency. Embrace the future of artificial intelligence with this expertly crafted resource at your fingertips.

Applied Machine Learning and High-Performance Computing on AWS

Author : Mani Khanuja
Publisher : Packt Publishing Ltd
ISBN 13 : 1803244445
Total Pages : 382 pages
Book Rating : 4.8/5 (32 download)

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Book Synopsis Applied Machine Learning and High-Performance Computing on AWS by : Mani Khanuja

Download or read book Applied Machine Learning and High-Performance Computing on AWS written by Mani Khanuja and published by Packt Publishing Ltd. This book was released on 2022-12-30 with total page 382 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build, train, and deploy large machine learning models at scale in various domains such as computational fluid dynamics, genomics, autonomous vehicles, and numerical optimization using Amazon SageMaker Key FeaturesUnderstand the need for high-performance computing (HPC)Build, train, and deploy large ML models with billions of parameters using Amazon SageMakerLearn best practices and architectures for implementing ML at scale using HPCBook Description Machine learning (ML) and high-performance computing (HPC) on AWS run compute-intensive workloads across industries and emerging applications. Its use cases can be linked to various verticals, such as computational fluid dynamics (CFD), genomics, and autonomous vehicles. This book provides end-to-end guidance, starting with HPC concepts for storage and networking. It then progresses to working examples on how to process large datasets using SageMaker Studio and EMR. Next, you'll learn how to build, train, and deploy large models using distributed training. Later chapters also guide you through deploying models to edge devices using SageMaker and IoT Greengrass, and performance optimization of ML models, for low latency use cases. By the end of this book, you'll be able to build, train, and deploy your own large-scale ML application, using HPC on AWS, following industry best practices and addressing the key pain points encountered in the application life cycle. What you will learnExplore data management, storage, and fast networking for HPC applicationsFocus on the analysis and visualization of a large volume of data using SparkTrain visual transformer models using SageMaker distributed trainingDeploy and manage ML models at scale on the cloud and at the edgeGet to grips with performance optimization of ML models for low latency workloadsApply HPC to industry domains such as CFD, genomics, AV, and optimizationWho this book is for The book begins with HPC concepts, however, it expects you to have prior machine learning knowledge. This book is for ML engineers and data scientists interested in learning advanced topics on using large datasets for training large models using distributed training concepts on AWS, deploying models at scale, and performance optimization for low latency use cases. Practitioners in fields such as numerical optimization, computation fluid dynamics, autonomous vehicles, and genomics, who require HPC for applying ML models to applications at scale will also find the book useful.

Cyber Security and Digital Forensics

Author : Nihar Ranjan Roy
Publisher : Springer Nature
ISBN 13 : 9819998115
Total Pages : 654 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Cyber Security and Digital Forensics by : Nihar Ranjan Roy

Download or read book Cyber Security and Digital Forensics written by Nihar Ranjan Roy and published by Springer Nature. This book was released on with total page 654 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Effective Machine Learning Teams

Author : David Tan
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098144597
Total Pages : 421 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Effective Machine Learning Teams by : David Tan

Download or read book Effective Machine Learning Teams written by David Tan and published by "O'Reilly Media, Inc.". This book was released on 2024-02-29 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain the valuable skills and techniques you need to accelerate the delivery of machine learning solutions. With this practical guide, data scientists, ML engineers, and their leaders will learn how to bridge the gap between data science and Lean product delivery in a practical and simple way. David Tan, Ada Leung, and Dave Colls show you how to apply time-tested software engineering skills and Lean product delivery practices to reduce toil and waste, shorten feedback loops, and improve your team's flow when building ML systems and products. Based on the authors' experience across multiple real-world data and ML projects, the proven techniques in this book will help your team avoid common traps in the ML world, so you can iterate and scale more quickly and reliably. You'll learn how to overcome friction and experience flow when delivering ML solutions. You'll also learn how to: Write automated tests for ML systems, containerize development environments, and refactor problematic codebases Apply MLOps and CI/CD practices to accelerate experimentation cycles and improve reliability of ML solutions Apply Lean delivery and product practices to improve your odds of building the right product for your users Identify suitable team structures and intra- and inter-team collaboration techniques to enable fast flow, reduce cognitive load, and scale ML within your organization

Building an Effective IoT Ecosystem for Your Business

Author : Sudhi R. Sinha
Publisher : Springer
ISBN 13 : 3319573918
Total Pages : 286 pages
Book Rating : 4.3/5 (195 download)

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Book Synopsis Building an Effective IoT Ecosystem for Your Business by : Sudhi R. Sinha

Download or read book Building an Effective IoT Ecosystem for Your Business written by Sudhi R. Sinha and published by Springer. This book was released on 2017-07-20 with total page 286 pages. Available in PDF, EPUB and Kindle. Book excerpt: This descriptive, practical guide explains how to build a commercially impactful, operationally effective and technically robust IoT ecosystem that takes advantage of the IoT revolution and drives business growth in the consumer IoT as well as industrial internet spaces. With this book, executives, business managers, developers and decision-makers are given the tools to make more informed decisions about IoT solution development, partner eco-system design, and the monetization of products and services. Security and privacy issues are also addressed. Readers will explore the design guidelines and technology choices required to build commercially viable IoT solutions, but also uncover the various monetization and business modeling for connected products.

The Machine Learning Solutions Architect Handbook

Author : David Ping
Publisher : Packt Publishing Ltd
ISBN 13 : 180512482X
Total Pages : 603 pages
Book Rating : 4.8/5 (51 download)

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Book Synopsis The Machine Learning Solutions Architect Handbook by : David Ping

Download or read book The Machine Learning Solutions Architect Handbook written by David Ping and published by Packt Publishing Ltd. This book was released on 2024-04-15 with total page 603 pages. Available in PDF, EPUB and Kindle. Book excerpt: Design, build, and secure scalable machine learning (ML) systems to solve real-world business problems with Python and AWS Purchase of the print or Kindle book includes a free PDF eBook Key Features Go in-depth into the ML lifecycle, from ideation and data management to deployment and scaling Apply risk management techniques in the ML lifecycle and design architectural patterns for various ML platforms and solutions Understand the generative AI lifecycle, its core technologies, and implementation risks Book DescriptionDavid Ping, Head of GenAI and ML Solution Architecture for global industries at AWS, provides expert insights and practical examples to help you become a proficient ML solutions architect, linking technical architecture to business-related skills. You'll learn about ML algorithms, cloud infrastructure, system design, MLOps , and how to apply ML to solve real-world business problems. David explains the generative AI project lifecycle and examines Retrieval Augmented Generation (RAG), an effective architecture pattern for generative AI applications. You’ll also learn about open-source technologies, such as Kubernetes/Kubeflow, for building a data science environment and ML pipelines before building an enterprise ML architecture using AWS. As well as ML risk management and the different stages of AI/ML adoption, the biggest new addition to the handbook is the deep exploration of generative AI. By the end of this book , you’ll have gained a comprehensive understanding of AI/ML across all key aspects, including business use cases, data science, real-world solution architecture, risk management, and governance. You’ll possess the skills to design and construct ML solutions that effectively cater to common use cases and follow established ML architecture patterns, enabling you to excel as a true professional in the field.What you will learn Apply ML methodologies to solve business problems across industries Design a practical enterprise ML platform architecture Gain an understanding of AI risk management frameworks and techniques Build an end-to-end data management architecture using AWS Train large-scale ML models and optimize model inference latency Create a business application using artificial intelligence services and custom models Dive into generative AI with use cases, architecture patterns, and RAG Who this book is for This book is for solutions architects working on ML projects, ML engineers transitioning to ML solution architect roles, and MLOps engineers. Additionally, data scientists and analysts who want to enhance their practical knowledge of ML systems engineering, as well as AI/ML product managers and risk officers who want to gain an understanding of ML solutions and AI risk management, will also find this book useful. A basic knowledge of Python, AWS, linear algebra, probability, and cloud infrastructure is required before you get started with this handbook.

Automated Machine Learning on AWS

Author : Trenton Potgieter
Publisher : Packt Publishing Ltd
ISBN 13 : 180181452X
Total Pages : 421 pages
Book Rating : 4.8/5 (18 download)

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Book Synopsis Automated Machine Learning on AWS by : Trenton Potgieter

Download or read book Automated Machine Learning on AWS written by Trenton Potgieter and published by Packt Publishing Ltd. This book was released on 2022-04-15 with total page 421 pages. Available in PDF, EPUB and Kindle. Book excerpt: Automate the process of building, training, and deploying machine learning applications to production with AWS solutions such as SageMaker Autopilot, AutoGluon, Step Functions, Amazon Managed Workflows for Apache Airflow, and more Key FeaturesExplore the various AWS services that make automated machine learning easierRecognize the role of DevOps and MLOps methodologies in pipeline automationGet acquainted with additional AWS services such as Step Functions, MWAA, and more to overcome automation challengesBook Description AWS provides a wide range of solutions to help automate a machine learning workflow with just a few lines of code. With this practical book, you'll learn how to automate a machine learning pipeline using the various AWS services. Automated Machine Learning on AWS begins with a quick overview of what the machine learning pipeline/process looks like and highlights the typical challenges that you may face when building a pipeline. Throughout the book, you'll become well versed with various AWS solutions such as Amazon SageMaker Autopilot, AutoGluon, and AWS Step Functions to automate an end-to-end ML process with the help of hands-on examples. The book will show you how to build, monitor, and execute a CI/CD pipeline for the ML process and how the various CI/CD services within AWS can be applied to a use case with the Cloud Development Kit (CDK). You'll understand what a data-centric ML process is by working with the Amazon Managed Services for Apache Airflow and then build a managed Airflow environment. You'll also cover the key success criteria for an MLSDLC implementation and the process of creating a self-mutating CI/CD pipeline using AWS CDK from the perspective of the platform engineering team. By the end of this AWS book, you'll be able to effectively automate a complete machine learning pipeline and deploy it to production. What you will learnEmploy SageMaker Autopilot and Amazon SageMaker SDK to automate the machine learning processUnderstand how to use AutoGluon to automate complicated model building tasksUse the AWS CDK to codify the machine learning processCreate, deploy, and rebuild a CI/CD pipeline on AWSBuild an ML workflow using AWS Step Functions and the Data Science SDKLeverage the Amazon SageMaker Feature Store to automate the machine learning software development life cycle (MLSDLC)Discover how to use Amazon MWAA for a data-centric ML processWho this book is for This book is for the novice as well as experienced machine learning practitioners looking to automate the process of building, training, and deploying machine learning-based solutions into production, using both purpose-built and other AWS services. A basic understanding of the end-to-end machine learning process and concepts, Python programming, and AWS is necessary to make the most out of this book.

Agile Machine Learning

Author : Eric Carter
Publisher : Apress
ISBN 13 : 1484251075
Total Pages : 257 pages
Book Rating : 4.4/5 (842 download)

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Book Synopsis Agile Machine Learning by : Eric Carter

Download or read book Agile Machine Learning written by Eric Carter and published by Apress. This book was released on 2019-08-21 with total page 257 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build resilient applied machine learning teams that deliver better data products through adapting the guiding principles of the Agile Manifesto. Bringing together talented people to create a great applied machine learning team is no small feat. With developers and data scientists both contributing expertise in their respective fields, communication alone can be a challenge. Agile Machine Learning teaches you how to deliver superior data products through agile processes and to learn, by example, how to organize and manage a fast-paced team challenged with solving novel data problems at scale, in a production environment. The authors’ approach models the ground-breaking engineering principles described in the Agile Manifesto. The book provides further context, and contrasts the original principles with the requirements of systems that deliver a data product. What You'll Learn Effectively run a data engineering team that is metrics-focused, experiment-focused, and data-focused Make sound implementation and model exploration decisions based on the data and the metrics Know the importance of data wallowing: analyzing data in real time in a group setting Recognize the value of always being able to measure your current state objectively Understand data literacy, a key attribute of a reliable data engineer, from definitions to expectations Who This Book Is For Anyone who manages a machine learning team, or is responsible for creating production-ready inference components. Anyone responsible for data project workflow of sampling data; labeling, training, testing, improving, and maintaining models; and system and data metrics will also find this book useful. Readers should be familiar with software engineering and understand the basics of machine learning and working with data.

Machine Learning for Societal Improvement, Modernization, and Progress

Author : Pendyala, Vishnu S.
Publisher : IGI Global
ISBN 13 : 1668440474
Total Pages : 307 pages
Book Rating : 4.6/5 (684 download)

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Book Synopsis Machine Learning for Societal Improvement, Modernization, and Progress by : Pendyala, Vishnu S.

Download or read book Machine Learning for Societal Improvement, Modernization, and Progress written by Pendyala, Vishnu S. and published by IGI Global. This book was released on 2022-06-24 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning has been fundamental to the growth and evolution of humanity and civilization. The same concepts of learning, applied to the tasks that machines can perform, are having a similar effect now. Machine learning is evolving computation and its applications like never before. It is now widely recognized that machine learning is playing a similar role to electricity in the late 19th and early 20th centuries in modernizing the world. From simple high school science projects to large-scale radio astronomy, machine learning has revolutionized it all—however, a few of the applications clearly stand out as transforming the world and opening up a new era. Machine Learning for Societal Improvement, Modernization, and Progress showcases the path-breaking applications of machine learning that are leading to the next generation of computing and living standards. The focus of the book is machine learning and its application to specific domains, which is resulting in substantial civilizational progress. Covering topics such as lifespan prediction, smart transportation networks, and socio-economic data, this premier reference source is a dynamic resource for data scientists, industry leaders, practitioners, students and faculty of higher education, sociologists, researchers, and academicians.

AWS Certified Solutions Architect - Foundational (SAF-C01)

Author :
Publisher : Cybellium
ISBN 13 : 1836798768
Total Pages : 232 pages
Book Rating : 4.8/5 (367 download)

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Book Synopsis AWS Certified Solutions Architect - Foundational (SAF-C01) by :

Download or read book AWS Certified Solutions Architect - Foundational (SAF-C01) written by and published by Cybellium . This book was released on with total page 232 pages. Available in PDF, EPUB and Kindle. Book excerpt: Welcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cutting-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com

Disruptive Cloud Computing and It

Author : Rajakumar Sampathkumar
Publisher : Xlibris Corporation
ISBN 13 : 1503566714
Total Pages : 348 pages
Book Rating : 4.5/5 (35 download)

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Book Synopsis Disruptive Cloud Computing and It by : Rajakumar Sampathkumar

Download or read book Disruptive Cloud Computing and It written by Rajakumar Sampathkumar and published by Xlibris Corporation. This book was released on 2015-05-26 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cloud Computing is a "daily spoken" and most commonly used terminology in every forum. Every conversation with a CIO has a reference to cloud computing. The objective of this book is to simplify cloud computing, explain what is cloud computings impact on Enterprise IT and how business should be prepared to leverage the benefits of cloud in the right way. THIS BOOK WILL BE YOUR KNOWLEDGE GATEWAY TO CLOUD COMPUTING AND NEXT GENERATION INFORMATION TECHNOLOGY MANAGEMENT. Besides core cloud computing concepts and process you will also be presented with latest technologies and tools available today to onboard your assets to cloud and manage cloud better. A cloud computing professional who has worked with several cloud providers and organizations of varied sizes writes this book so expect real life examples, techniques, process and working models for every scenario in strategizing, migrating and managing IT infrastructure in the cloud. The book is carefully structured to gradually take the readers through the basics of cloud computing concepts, terminologies, implementation and management techniques through traditional IT management so that readers can easily connect ends. Several transformational, working models and best practices are discussed throughout the book. If you are looking for a book on cloud computing, #thecloudbook is the right book for you. If you have already purchased any books on cloud computing, read #thecloudbook and then go through the other books, you will understand the other books better. #thecloudbook is a must for every IT professional.