Author: Stephen Fleming
Publisher: Stephen Fleming
ISBN:
Category : Computers
Languages : en
Pages : 112
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Book Description
What comes to your mind after reading the below statements from a renowned industry research firm? It is predicted that a large enterprise exclusive use of AIOps and digital experience monitoring tools to monitor applications and infrastructure will rise from 5% in 2018 to 30% in 2023. Also, Only 47% of machine learning models are making it into production (Comes MLOPS!) Do you have similar thoughts? Is it just a new Buzzword or repackaging of the existing system? If it’s for real, how is it going to impact the Business/Industry? How my business or job would get impacted? If it has just started, how can I leverage from wherever I am? Which are the major players/startups in this area? Depending on your role, it may be useful for you to know about AIOPS & MLOPS: If you are a Business Consultant trying to make the system more efficient and profitable, reaping the benefits of Automation in your application development process If you are a Technology Consultant and want to make your operation more Agile, Automated and easily deployable If you are a Technology Professional looking for a role in these upcoming areas to be an early adopter in your organization or just starting your career and want to understand the ecosystem If you are from HR or Training field and want to understand the job/Training requirements for these upcoming roles Beyond the apparent hustle and bustle of buzzwords and nomenclature every year, I genuinely believe that AI would drastically change the software development and deployment model in the next two years, and all these new startups would drive this change. It’s astonishing how fast this cycle is moving. Especially for us who had seen the world before the internet came into our daily lives!!This book is my attempt to update you on the unfolding story of AIOPS and MLOPS as “story till now. “ So here is to our Continuous Learning and Progress! Cheers.
Author: Deepa Jose
Publisher: CRC Press
ISBN: 1040041159
Category : Computers
Languages : en
Pages : 419
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Book Description
The purpose of this book is to discuss the trends and key drivers of Internet of Things (IoT) and artificial intelligence (AI) for automation in Industry 4.0. IoT and AI are transforming the industry thus accelerating efficiency and forging a more reliable automated enterprise. AI-driven IoT systems for Industry 4.0 explore current research to be carried out in the cutting-edge areas of AI for advanced analytics, integration of industrial IoT (IIoT) solutions and Edge components, automation in cyber-physical systems, world leading Industry 4.0 frameworks and adaptive supply chains, etc. A thorough exploration of Industry 4.0 is provided, focusing on the challenges of digital transformation and automation. It covers digital connectivity, sensors, and the integration of intelligent thinking and data science. Emphasizing the significance of AI, the chapter delves into optimal decision-making in Industry 4.0. It extensively examines automation and hybrid edge computing architecture, highlighting their applications. The narrative then shifts to IIoT and edge AI, exploring their convergence and the use of edge AI for visual insights in smart factories. The book concludes by discussing the role of AI in constructing digital twins, speeding up product development lifecycles, and offering insights for decision-making in smart factories. Throughout, the emphasis remains on the transformative impact of deep learning and AI in automating and accelerating manufacturing processes within the context of Industry 4.0. This book is intended for undergraduates, postgraduates, academicians, researchers, and industry professionals in industrial and computer engineering.
Author: Jeroen Mulder
Publisher: Packt Publishing Ltd
ISBN: 1801811709
Category : Computers
Languages : en
Pages : 289
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Book Description
An architect's guide to designing, implementing, and integrating DevOps in the enterprise Key FeaturesDesign a DevOps architecture that is aligned with the overall enterprise architectureDesign systems that are ready for AIOps and make the move toward NoOpsArchitect and implement DevSecOps pipelines, securing the DevOps enterpriseBook Description Digital transformation is the new paradigm in enterprises, but the big question remains: is the enterprise ready for transformation using native technology embedded in Agile/DevOps? With this book, you'll see how to design, implement, and integrate DevOps in the enterprise architecture while keeping the Ops team on board and remaining resilient. The focus of the book is not to introduce the hundreds of different tools that are available for implementing DevOps, but instead to show you how to create a successful DevOps architecture. This book provides an architectural overview of DevOps, AIOps, and DevSecOps – the three domains that drive and accelerate digital transformation. Complete with step-by-step explanations of essential concepts, practical examples, and self-assessment questions, this DevOps book will help you to successfully integrate DevOps into enterprise architecture. You'll learn what AIOps is and what value it can bring to an enterprise. Lastly, you will learn how to integrate security principles such as zero-trust and industry security frameworks into DevOps with DevSecOps. By the end of this DevOps book, you'll be able to develop robust DevOps architectures, know which toolsets you can use for your DevOps implementation, and have a deeper understanding of next-level DevOps by implementing Site Reliability Engineering (SRE). What you will learnCreate DevOps architecture and integrate it with the enterprise architectureDiscover how DevOps can add value to the quality of IT deliveryExplore strategies to scale DevOps for an enterpriseArchitect SRE for an enterprise as next-level DevOpsUnderstand AIOps and what value it can bring to an enterpriseCreate your AIOps architecture and integrate it into DevOpsCreate your DevSecOps architecture and integrate it with the existing DevOps setupApply zero-trust principles and industry security frameworks to DevOpsWho this book is for This book is for enterprise architects and consultants who want to design DevOps systems for the enterprise. It provides an architectural overview of DevOps, AIOps, and DevSecOps. If you're looking to learn about the implementation of various tools within the DevOps toolchain in detail, this book is not for you.
Author: Tom Taulli
Publisher: Apress
ISBN: 1484257294
Category : Computers
Languages : en
Pages : 359
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Book Description
While Robotic Process Automation (RPA) has been around for about 20 years, it has hit an inflection point because of the convergence of cloud computing, big data and AI. This book shows you how to leverage RPA effectively in your company to automate repetitive and rules-based processes, such as scheduling, inputting/transferring data, cut and paste, filling out forms, and search. Using practical aspects of implementing the technology (based on case studies and industry best practices), you’ll see how companies have been able to realize substantial ROI (Return On Investment) with their implementations, such as by lessening the need for hiring or outsourcing. By understanding the core concepts of RPA, you’ll also see that the technology significantly increases compliance – leading to fewer issues with regulations – and minimizes costly errors. RPA software revenues have recently soared by over 60 percent, which is the fastest ramp in the tech industry, and they are expected to exceed $1 billion by the end of 2019. It is generally seamless with legacy IT environments, making it easier for companies to pursue a strategy of digital transformation and can even be a gateway to AI. The Robotic Process Automation Handbook puts everything you need to know into one place to be a part of this wave. What You'll Learn Develop the right strategy and planDeal with resistance and fears from employeesTake an in-depth look at the leading RPA systems, including where they are most effective, the risks and the costsEvaluate an RPA system Who This Book Is For IT specialists and managers at mid-to-large companies
Author: Ian Sommerville
Publisher:
ISBN: 9781292376349
Category : Computer software
Languages : en
Pages :
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Book Description
Author: Mark Treveil
Publisher: "O'Reilly Media, Inc."
ISBN: 1098116429
Category : Computers
Languages : en
Pages : 163
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Book Description
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
Author: Prateek Joshi
Publisher: Packt Publishing Ltd
ISBN: 1786469677
Category : Computers
Languages : en
Pages : 437
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Book Description
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
Author: Bhaskar Ghosh
Publisher: McGraw Hill Professional
ISBN: 1260473309
Category : Business & Economics
Languages : en
Pages : 289
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Book Description
From the global automation leaders at Accenture—the first-ever comprehensive blueprint for how to use and scale AI-powered intelligent automation in the enterprise to gain competitive advantage through faster speed to market, improved product quality, higher efficiency, and an elevated customer experience. Many companies were already implementing limited levels of automation when the pandemic hit. But the need to rapidly change business processes and how organizations work resulted in the compression of a decade’s worth of digital transformation into a matter of months. Technology suddenly became the essential element for rapid organizational change and the creation of 360-degree value benefiting all stakeholders. Businesses are faced with the imperative to embrace that change or risk being left behind. In The Automation Advantage, global enterprise technology and automation veterans Bhaskar Ghosh, Rajendra Prasad, and Gayathri Pallail give business leaders and managers the action plan they need to execute a strategic agenda that enables them to quickly and confidently scale their automation and AI initiatives. This practical and highly accessible implementation guide answers leaders’ burning questions, such as: How do I identify and prioritize automation opportunities? How do I assess my legacy systems and data issues? How do I derive full value out of my technology investments and automation efforts? How can I inspire my employees to embrace change and the new opportunities presented by automation? The Automation Advantage goes beyond optimizing process to using AI to transform almost any business activity in any industry to make it faster, more streamlined, cost efficient, and customer-focused—vastly improving overall productivity and performance. Featuring case studies of successful automation solutions, this indispensable road map includes guiding principles for technology, governance, culture, and leadership change. It offers a human-centric approach to AI and automation that leads to sustainable transformation and measurable business results.
Author: Hannes Hapke
Publisher: "O'Reilly Media, Inc."
ISBN: 1492053147
Category : Computers
Languages : en
Pages : 358
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Book Description
Companies are spending billions on machine learning projects, but it’s money wasted if the models can’t be deployed effectively. In this practical guide, Hannes Hapke and Catherine Nelson walk you through the steps of automating a machine learning pipeline using the TensorFlow ecosystem. You’ll learn the techniques and tools that will cut deployment time from days to minutes, so that you can focus on developing new models rather than maintaining legacy systems. Data scientists, machine learning engineers, and DevOps engineers will discover how to go beyond model development to successfully productize their data science projects, while managers will better understand the role they play in helping to accelerate these projects. Understand the steps to build a machine learning pipeline Build your pipeline using components from TensorFlow Extended Orchestrate your machine learning pipeline with Apache Beam, Apache Airflow, and Kubeflow Pipelines Work with data using TensorFlow Data Validation and TensorFlow Transform Analyze a model in detail using TensorFlow Model Analysis Examine fairness and bias in your model performance Deploy models with TensorFlow Serving or TensorFlow Lite for mobile devices Learn privacy-preserving machine learning techniques
Author: Valliappa Lakshmanan
Publisher: O'Reilly Media
ISBN: 1098115759
Category : Computers
Languages : en
Pages : 408
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Book Description
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
