Download or read book Combining DataOps MLOps and DevOps written by Kalpesh Parikh and published by Bpb Publications. This book was released on 2022-05-16 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerate the delivery of software, data, and machine learning KEY FEATURES ● Each chapter harmonizes the DevOps, Data Engineering, and Optimized Machine Learning cultures. ● Equips readers with AGILE skills to continuously re-prioritize production backlogs. ● Containerization, Docker, Kubernetes, DataOps, and MLOps are all rolled together. DESCRIPTION This book instructs readers on how to operationalize the creation of systems, software applications, and business information using the best practices of DevOps, DataOps, and MLOps, among other things. From software unit packaging code and its dependencies to automating the software development lifecycle and deployment, the book provides a learning roadmap that begins with the basics and progresses to advanced topics. This book teaches you how to create a culture of cooperation, affinity, and tooling at scale using DevOps, Docker, Kubernetes, Data Engineering, and Machine Learning. Microservices design, setting up clusters and maintaining them, processing data pipelines, and automating operations with machine learning are all topics that will aid you in your career. When you use each of the xOps methods described in the book, you will notice a clear shift in your understanding of system development. Throughout the book, you will see how every stage of software development is modernized with the most up-to-date technologies and the most effective project management approaches. WHAT YOU WILL LEARN ● Learn about the Packaging code and all its dependencies in a container. ● Utilize DevOps to automate every stage of software development. ● Learn how to create Microservices that are focused on a specific issue. ● Utilize Kubernetes to containerize applications in a variety of settings. ● Using DataOps, you can align people, processes, and technology. WHO THIS BOOK IS FOR This book is meant for the Software Engineering team, Data Professionals, IT Operations and Application Development Team with prior knowledge in software development.

Download or read book Combining DataOps MLOps and DevOps written by Dr. Kalpesh Parikh and published by BPB Publications. This book was released on 2022-05-16 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accelerate the delivery of software, data, and machine learning KEY FEATURES ● Each chapter harmonizes the DevOps, Data Engineering, and Optimized Machine Learning cultures. ● Equips readers with AGILE skills to continuously re-prioritize production backlogs. ● Containerization, Docker, Kubernetes, DataOps, and MLOps are all rolled together. DESCRIPTION This book instructs readers on how to operationalize the creation of systems, software applications, and business information using the best practices of DevOps, DataOps, and MLOps, among other things. From software unit packaging code and its dependencies to automating the software development lifecycle and deployment, the book provides a learning roadmap that begins with the basics and progresses to advanced topics. This book teaches you how to create a culture of cooperation, affinity, and tooling at scale using DevOps, Docker, Kubernetes, Data Engineering, and Machine Learning. Microservices design, setting up clusters and maintaining them, processing data pipelines, and automating operations with machine learning are all topics that will aid you in your career. When you use each of the xOps methods described in the book, you will notice a clear shift in your understanding of system development. Throughout the book, you will see how every stage of software development is modernized with the most up-to-date technologies and the most effective project management approaches. WHAT YOU WILL LEARN ● Learn about the Packaging code and all its dependencies in a container. ● Utilize DevOps to automate every stage of software development. ● Learn how to create Microservices that are focused on a specific issue. ● Utilize Kubernetes to containerize applications in a variety of settings. ● Using DataOps, you can align people, processes, and technology. WHO THIS BOOK IS FOR This book is meant for the Software Engineering team, Data Professionals, IT Operations and Application Development Team with prior knowledge in software development. TABLE OF CONTENTS 1. Container – Containerization is the New Virtualization 2. Docker with Containers for Developing and Deploying Software 3. DevOps to Build at Scale a Culture of Collaboration, Affinity, and Tooling 4. Docker Containers for Microservices Architecture Design 5. Kubernetes – The Cluster Manager for Container 6. Data Engineering with DataOps 7. MLOps: Engineering Machine Learning Operations 8. xOps Best Practices

Download or read book It s All Analytics Part III written by Scott Burk and published by CRC Press. This book was released on 2023-09-15 with total page 248 pages. Available in PDF, EPUB and Kindle. Book excerpt: Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially the last 25 years, there has been an explosion of terms and methods born that automate and improve decision-making and operations. One term, called "analytics," is an overarching description of a compilation of methodologies. But artificial intelligence (AI), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology, terminology? Extending on the foundations introduced in the first book, this book illustrates how professionals in healthcare, business, and government are applying these disciplines, methods, and technologies. The goal of this book is to get leaders and practitioners to start thinking about how they may deploy techniques outside their function or industry into their domain. Application of modern technology into new areas is one of the fastest, most effective ways to improve results. By providing a rich set of examples, this book fosters creativity in the application and use of AI and analytics in innovative ways.

Download or read book Databricks ML in Action written by Stephanie Rivera and published by Packt Publishing Ltd. This book was released on 2024-05-17 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with autogenerating code, deploying ML algorithms, and leveraging various ML lifecycle features on the Databricks Platform, guided by best practices and reusable code for you to try, alter, and build on Key Features Build machine learning solutions faster than peers only using documentation Enhance or refine your expertise with tribal knowledge and concise explanations Follow along with code projects provided in GitHub to accelerate your projects Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover what makes the Databricks Data Intelligence Platform the go-to choice for top-tier machine learning solutions. Written by a team of industry experts at Databricks with decades of combined experience in big data, machine learning, and data science, Databricks ML in Action presents cloud-agnostic, end-to-end examples with hands-on illustrations of executing data science, machine learning, and generative AI projects on the Databricks Platform. You’ll develop expertise in Databricks' managed MLflow, Vector Search, AutoML, Unity Catalog, and Model Serving as you learn to apply them practically in everyday workflows. This Databricks book not only offers detailed code explanations but also facilitates seamless code importation for practical use. You’ll discover how to leverage the open-source Databricks platform to enhance learning, boost skills, and elevate productivity with supplemental resources. By the end of this book, you'll have mastered the use of Databricks for data science, machine learning, and generative AI, enabling you to deliver outstanding data products.What you will learn Set up a workspace for a data team planning to perform data science Monitor data quality and detect drift Use autogenerated code for ML modeling and data exploration Operationalize ML with feature engineering client, AutoML, VectorSearch, Delta Live Tables, AutoLoader, and Workflows Integrate open-source and third-party applications, such as OpenAI's ChatGPT, into your AI projects Communicate insights through Databricks SQL dashboards and Delta Sharing Explore data and models through the Databricks marketplace Who this book is for This book is for machine learning engineers, data scientists, and technical managers seeking hands-on expertise in implementing and leveraging the Databricks Data Intelligence Platform and its Lakehouse architecture to create data products.

Download or read book Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment written by Jean-Michel Bruel and published by Springer Nature. This book was released on 2020-01-18 with total page 221 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes revised selected papers of the Second International Workshop on Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, DEVOPS 2019, held at the Château de Villebrumier, France, in May 2019. The 15 papers presented in this volume were carefully reviewed and selected from 19 submissions. They cover a wide range of problems arising from DevOps and related approaches: current tools, rapid development-deployment processes, modeling frameworks, anomaly detection in software releases, DevDataOps, microservices, and related topics.

Download or read book Practical DataOps written by Harvinder Atwal and published by Apress. This book was released on 2019-12-09 with total page 289 pages. Available in PDF, EPUB and Kindle. Book excerpt: Gain a practical introduction to DataOps, a new discipline for delivering data science at scale inspired by practices at companies such as Facebook, Uber, LinkedIn, Twitter, and eBay. Organizations need more than the latest AI algorithms, hottest tools, and best people to turn data into insight-driven action and useful analytical data products. Processes and thinking employed to manage and use data in the 20th century are a bottleneck for working effectively with the variety of data and advanced analytical use cases that organizations have today. This book provides the approach and methods to ensure continuous rapid use of data to create analytical data products and steer decision making. Practical DataOps shows you how to optimize the data supply chain from diverse raw data sources to the final data product, whether the goal is a machine learning model or other data-orientated output. The book provides an approach to eliminate wasted effort and improve collaboration between data producers, data consumers, and the rest of the organization through the adoption of lean thinking and agile software development principles. This book helps you to improve the speed and accuracy of analytical application development through data management and DevOps practices that securely expand data access, and rapidly increase the number of reproducible data products through automation, testing, and integration. The book also shows how to collect feedback and monitor performance to manage and continuously improve your processes and output. What You Will LearnDevelop a data strategy for your organization to help it reach its long-term goals Recognize and eliminate barriers to delivering data to users at scale Work on the right things for the right stakeholders through agile collaboration Create trust in data via rigorous testing and effective data management Build a culture of learning and continuous improvement through monitoring deployments and measuring outcomes Create cross-functional self-organizing teams focused on goals not reporting lines Build robust, trustworthy, data pipelines in support of AI, machine learning, and other analytical data products Who This Book Is For Data science and advanced analytics experts, CIOs, CDOs (chief data officers), chief analytics officers, business analysts, business team leaders, and IT professionals (data engineers, developers, architects, and DBAs) supporting data teams who want to dramatically increase the value their organization derives from data. The book is ideal for data professionals who want to overcome challenges of long delivery time, poor data quality, high maintenance costs, and scaling difficulties in getting data science output and machine learning into customer-facing production.

Download or read book More Than My Title written by Sarabeth Berk and published by Networlding Publishing. This book was released on 2020-04-12 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you do more than one thing for work, then you are more than one thing. If this describes you, then you may be a hybrid professional. Until recently, hybrids have been hidden in the workforce. But today and moving forward, the secret is out. In today's world, professional identity is no longer just about being an expert or a generalist. Now, workers can be both. These hybrid professionals have unique talents that defy conventional labels because they work at the intersections of their multiple identities. Discover how hybrid professionals are revolutionizing the workforce and leading exciting, one-of-a-kind work. If you're a jack-of-all-trades or trying to figure out what differentiates you from others, give yourself permission to become a hybrid professional and be more than your title.

Download or read book Machine Learning Design Patterns written by Valliappa Lakshmanan and published by O'Reilly Media. This book was released on 2020-10-15 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly

Download or read book DevOps for Developers written by Michael Httermann and published by Apress. This book was released on 2012-10-24 with total page 183 pages. Available in PDF, EPUB and Kindle. Book excerpt: DevOps for Developers delivers a practical, thorough introduction to approaches, processes and tools to foster collaboration between software development and operations. Efforts of Agile software development often end at the transition phase from development to operations. This book covers the delivery of software, this means “the last mile”, with lean practices for shipping the software to production and making it available to the end users, together with the integration of operations with earlier project phases (elaboration, construction, transition). DevOps for Developers describes how to streamline the software delivery process and improve the cycle time (that is the time from inception to delivery). It will enable you to deliver software faster, in better quality and more aligned with individual requirements and basic conditions. And above all, work that is aligned with the “DevOps” approach makes even more fun! Provides patterns and toolchains to integrate software development and operations Delivers an one-stop shop for kick-starting with DevOps Provides guidance how to streamline the software delivery process

Download or read book Introducing MLOps written by Mark Treveil and published by "O'Reilly Media, Inc.". This book was released on 2020-11-30 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: More than half of the analytics and machine learning (ML) models created by organizations today never make it into production. Some of the challenges and barriers to operationalization are technical, but others are organizational. Either way, the bottom line is that models not in production can't provide business impact. This book introduces the key concepts of MLOps to help data scientists and application engineers not only operationalize ML models to drive real business change but also maintain and improve those models over time. Through lessons based on numerous MLOps applications around the world, nine experts in machine learning provide insights into the five steps of the model life cycle--Build, Preproduction, Deployment, Monitoring, and Governance--uncovering how robust MLOps processes can be infused throughout. This book helps you: Fulfill data science value by reducing friction throughout ML pipelines and workflows Refine ML models through retraining, periodic tuning, and complete remodeling to ensure long-term accuracy Design the MLOps life cycle to minimize organizational risks with models that are unbiased, fair, and explainable Operationalize ML models for pipeline deployment and for external business systems that are more complex and less standardized

Download or read book The Phoenix Project written by Gene Kim and published by IT Revolution. This book was released on 2018-02-06 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: ***Over a half-million sold! And available now, the Wall Street Journal Bestselling sequel The Unicorn Project*** “Every person involved in a failed IT project should be forced to read this book.”—TIM O'REILLY, Founder & CEO of O'Reilly Media “The Phoenix Project is a must read for business and IT executives who are struggling with the growing complexity of IT.”—JIM WHITEHURST, President and CEO, Red Hat, Inc. Five years after this sleeper hit took on the world of IT and flipped it on it's head, the 5th Anniversary Edition of The Phoenix Project continues to guide IT in the DevOps revolution. In this newly updated and expanded edition of the bestselling The Phoenix Project, co-author Gene Kim includes a new afterword and a deeper delve into the Three Ways as described in The DevOps Handbook. Bill, an IT manager at Parts Unlimited, has been tasked with taking on a project critical to the future of the business, code named Phoenix Project. But the project is massively over budget and behind schedule. The CEO demands Bill must fix the mess in ninety days or else Bill's entire department will be outsourced. With the help of a prospective board member and his mysterious philosophy of The Three Ways, Bill starts to see that IT work has more in common with a manufacturing plant work than he ever imagined. With the clock ticking, Bill must organize work flow streamline interdepartmental communications, and effectively serve the other business functions at Parts Unlimited. In a fast-paced and entertaining style, three luminaries of the DevOps movement deliver a story that anyone who works in IT will recognize. Readers will not only learn how to improve their own IT organizations, they'll never view IT the same way again. “This book is a gripping read that captures brilliantly the dilemmas that face companies which depend on IT, and offers real-world solutions.”—JEZ HUMBLE, Co-author of Continuous Delivery, Lean Enterprise, Accelerate, and The DevOps Handbook

Download or read book 97 Things Every Data Engineer Should Know written by Tobias Macey and published by "O'Reilly Media, Inc.". This book was released on 2021-06-11 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take advantage of today's sky-high demand for data engineers. With this in-depth book, current and aspiring engineers will learn powerful real-world best practices for managing data big and small. Contributors from notable companies including Twitter, Google, Stitch Fix, Microsoft, Capital One, and LinkedIn share their experiences and lessons learned for overcoming a variety of specific and often nagging challenges. Edited by Tobias Macey, host of the popular Data Engineering Podcast, this book presents 97 concise and useful tips for cleaning, prepping, wrangling, storing, processing, and ingesting data. Data engineers, data architects, data team managers, data scientists, machine learning engineers, and software engineers will greatly benefit from the wisdom and experience of their peers. Topics include: The Importance of Data Lineage - Julien Le Dem Data Security for Data Engineers - Katharine Jarmul The Two Types of Data Engineering and Data Engineers - Jesse Anderson Six Dimensions for Picking an Analytical Data Warehouse - Gleb Mezhanskiy The End of ETL as We Know It - Paul Singman Building a Career as a Data Engineer - Vijay Kiran Modern Metadata for the Modern Data Stack - Prukalpa Sankar Your Data Tests Failed! Now What? - Sam Bail

Download or read book Data Engineering on Azure written by Vlad Riscutia and published by Simon and Schuster. This book was released on 2021-08-17 with total page 334 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a data platform to the industry-leading standards set by Microsoft’s own infrastructure. Summary In Data Engineering on Azure you will learn how to: Pick the right Azure services for different data scenarios Manage data inventory Implement production quality data modeling, analytics, and machine learning workloads Handle data governance Using DevOps to increase reliability Ingesting, storing, and distributing data Apply best practices for compliance and access control Data Engineering on Azure reveals the data management patterns and techniques that support Microsoft’s own massive data infrastructure. Author Vlad Riscutia, a data engineer at Microsoft, teaches you to bring an engineering rigor to your data platform and ensure that your data prototypes function just as well under the pressures of production. You'll implement common data modeling patterns, stand up cloud-native data platforms on Azure, and get to grips with DevOps for both analytics and machine learning. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Build secure, stable data platforms that can scale to loads of any size. When a project moves from the lab into production, you need confidence that it can stand up to real-world challenges. This book teaches you to design and implement cloud-based data infrastructure that you can easily monitor, scale, and modify. About the book In Data Engineering on Azure you’ll learn the skills you need to build and maintain big data platforms in massive enterprises. This invaluable guide includes clear, practical guidance for setting up infrastructure, orchestration, workloads, and governance. As you go, you’ll set up efficient machine learning pipelines, and then master time-saving automation and DevOps solutions. The Azure-based examples are easy to reproduce on other cloud platforms. What's inside Data inventory and data governance Assure data quality, compliance, and distribution Build automated pipelines to increase reliability Ingest, store, and distribute data Production-quality data modeling, analytics, and machine learning About the reader For data engineers familiar with cloud computing and DevOps. About the author Vlad Riscutia is a software architect at Microsoft. Table of Contents 1 Introduction PART 1 INFRASTRUCTURE 2 Storage 3 DevOps 4 Orchestration PART 2 WORKLOADS 5 Processing 6 Analytics 7 Machine learning PART 3 GOVERNANCE 8 Metadata 9 Data quality 10 Compliance 11 Distributing data

Download or read book Machine Learning Bookcamp written by Alexey Grigorev and published by Simon and Schuster. This book was released on 2021-11-23 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Time to flex your machine learning muscles! Take on the carefully designed challenges of the Machine Learning Bookcamp and master essential ML techniques through practical application. Summary In Machine Learning Bookcamp you will: Collect and clean data for training models Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow Apply ML to complex datasets with images Deploy ML models to a production-ready environment The only way to learn is to practice! In Machine Learning Bookcamp, you’ll create and deploy Python-based machine learning models for a variety of increasingly challenging projects. Taking you from the basics of machine learning to complex applications such as image analysis, each new project builds on what you’ve learned in previous chapters. You’ll build a portfolio of business-relevant machine learning projects that hiring managers will be excited to see. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Master key machine learning concepts as you build actual projects! Machine learning is what you need for analyzing customer behavior, predicting price trends, evaluating risk, and much more. To master ML, you need great examples, clear explanations, and lots of practice. This book delivers all three! About the book Machine Learning Bookcamp presents realistic, practical machine learning scenarios, along with crystal-clear coverage of key concepts. In it, you’ll complete engaging projects, such as creating a car price predictor using linear regression and deploying a churn prediction service. You’ll go beyond the algorithms and explore important techniques like deploying ML applications on serverless systems and serving models with Kubernetes and Kubeflow. Dig in, get your hands dirty, and have fun building your ML skills! What's inside Collect and clean data for training models Use popular Python tools, including NumPy, Scikit-Learn, and TensorFlow Deploy ML models to a production-ready environment About the reader Python programming skills assumed. No previous machine learning knowledge is required. About the author Alexey Grigorev is a principal data scientist at OLX Group. He runs DataTalks.Club, a community of people who love data. Table of Contents 1 Introduction to machine learning 2 Machine learning for regression 3 Machine learning for classification 4 Evaluation metrics for classification 5 Deploying machine learning models 6 Decision trees and ensemble learning 7 Neural networks and deep learning 8 Serverless deep learning 9 Serving models with Kubernetes and Kubeflow

Download or read book IT Infrastructure Automation Using Ansible written by Waqas Irtaza and published by BPB Publications. This book was released on 2021-09-30 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Expert solutions to automate routine IT tasks using Ansible. KEY FEATURES ● Single handy guide for all IT teams to bring automation throughout the enterprise. ● In-depth practical demonstration of various automation use-cases on the IT infrastructure. ● Expert-led guidelines and best practices to write Ansible playbooks without any errors. DESCRIPTION This book deals with all aspects of Ansible IT infrastructure automation. While reading this book, you should look for automation opportunities in your current role and automate time-consuming and repetitive tasks using Ansible. This book contains Ansible fundamentals assuming you are totally new to Ansible. Proper instructions for setting up the laboratory environment to implement each concept are explained and covered in detail. This book is equipped with practical examples, use-cases and modules on the network. The system and cloud management are practically demonstrated in the book. You will learn to automate all the common administrative tasks throughout the entire IT infrastructure. This book will help establish and build the proficiency of your automation skills, and you can start making the best use of Ansible in enterprise automation. WHAT WILL YOU LEARN ● Install Ansible and learn the fundamentals. ● Use practical examples and learn about the loop, conditional statements, and variables. ● Understand the Ansible network modules and how to apply them in our day-to-day network management. ● Learn to automate the Windows and Linux infrastructure using Ansible. ● Automate routine administrative tasks for AWS, Azure, Google Cloud. ● Explore how to use Ansible for Docker and Kubernetes. WHO THIS BOOK IS FOR This book is for all IT students and professionals who want to manage or plan to administer the IT infrastructure. Knowing the basic Linux command-line would be good although not mandatory. TABLE OF CONTENTS 1. Up and Running with Ansible 2. Ansible Basics 3. Ansible Advance Concepts 4. Ansible for Network Administration 5. Ansible for System Administration 6. Ansible for Cloud Administration 7. Ansible Tips and Tricks

Download or read book 2018 IEEE International Congress on Big Data BigData Congress written by IEEE Staff and published by . This book was released on 2018-07-02 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: ig Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc ), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions

Download or read book Working Out Loud written by John Stepper and published by . This book was released on 2015-06-10 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Would you like more out of work and life? Working Out Loud offers you ways to take control and make your own luck. Instead of playing career roulette, you invest in deepening relationships and developing your skills. Instead of networking to get something, you lead with generosity. To further improve your odds, you make your work visible and frame it as a contribution. Combined, these elements form a powerful approach to work and life. In Working Out Loud, you'll learn about research supporting this approach and read stories of people who've changed their lives by adopting it. Then you'll go through a twelve-week mastery program to put the approach into practice yourself and turn that practice into a sustainable habit.