- Table View
- List View
Enhancing LAN Performance
by Gilbert HeldEnhancing LAN Performance, Fourth Edition explains how to connect geographically separated LANs with appropriate bandwidth, the issues to consider when weighing the use of multiport or dualport devices, how to estimate traffic for new networks, the effects of configuration changes on the performance of Ethernet and Token Ring networks, the design o
Enhancing Microsoft Content Management Server with ASP.NET 2.0
by Lim Mei YingThe book is written for developers who work with Microsoft Content Management Server, and want to update their skills to take advantage of the latest offerings in ASP.NET. If you are an MCMS developer who hasn't yet got into ASP.NET 2.0, this book is an ideal introduction to the most exciting features of ASP.NET 2.0, and how you can make them work for you.
Enhancing Productivity with Notion: Save time on projects by supercharging your productivity with Notion's powerful features and templates
by Danny HatcherWritten by an experienced Notion Ambassador, this book helps you become proficient with the features, functions, and flexibility of the Notion app to make work and personal life easierKey FeaturesCreate accounts, workspaces, and dashboards using all of Notion's flexible featuresDevelop the skills you need to work in various contexts, while working collaboratively with othersUse basic and advanced blocks, databases, and functions to optimize a workflow that works for youBook DescriptionNotion is note-taking, wiki management, and task and project management software that gives you control of your working environment. By creating pages using a variety of block types and database styles, the possibilities are endless. This book will help you overcome challenges in managing large projects using Notion and creating documents using real-time updates with a great deal of flexibility, allowing everyone to have a customized view as per their needs.With this book, you'll become well-versed with Notion, where you'll learn how to access, create, and change a workspace utilizing all the blocks, database views and properties, and advanced features and functions. From a table or list view to a Kanban board or gallery view, you'll get to explore several database options available in Notion. You'll learn the skills to build pages, customize the aesthetics, create templates, and store, organize, and surface information through databases, all while building a system and workflow that works for you in your context. The book will also demonstrate how to import and export information and combine Notion with other tools using the API.By the end of this book, you'll be able to create a task management system, project management system, or any other system while combining it with other tools that speed up your work for better efficiency.What you will learnUnderstand how to set up and build on any deviceNavigate, share and alter the appearance of your workspaceImport and export data to and from NotionUnderstand how to use all the database views, filters, sorts, and propertiesCreate task, wiki, and project management systemsConnect Notion to third-party applications with the APIWho this book is forBusiness users, power users, IT professionals, or anyone from a non-technical background looking to use Notion to increase their productivity will find this note-taking book useful.
Enhancing Reflection within Situated Learning: Incorporating Mindfulness As An Instructional Strategy (Springerbriefs In Educational Communications And Technology Ser.)
by Alexis M. Stoner Katherine S. CennamoThis innovative brief provides guidance on promoting reflection in situated learning by incorporating mindfulness strategies, tapping into a surge of research interest in exploring mindfulness as an instructional strategy associated with positive learning outcomes. It illustrates the benefits of continuous reflection within situated learning and how mindfulness can be incorporated before, during, and after the learning experience to enhance the reflective experience. Critically, the authors present a new conceptual model that synthesizes theories and methods from three different areas of study—mindfulness, situated learning, and reflection— to provide a new perspective and instructional approach that has great potential to positively impact outcomes in situated learning.Among the other topics covered:• Strategies for reflection in situated learning.• Strategies for reflection-in-action in situated learning.• Mindfulness strategies for situated learning.• A conceptual model incorporating mindfulness to enhance reflection.Enhancing Reflection within Situated Learning is an exciting and pioneering resource that offers practical guidance to educators and instructional designers interested in incorporating methods and approaches for integrating mindfulness and reflection across instructional environments.
Enhancing Surrogate-Based Optimization Through Parallelization (Studies in Computational Intelligence #1099)
by Frederik RehbachThis book presents a solution to the challenging issue of optimizing expensive-to-evaluate industrial problems such as the hyperparameter tuning of machine learning models. The approach combines two well-established concepts, Surrogate-Based Optimization (SBO) and parallelization, to efficiently search for optimal parameter setups with as few function evaluations as possible.Through in-depth analysis, the need for parallel SBO solvers is emphasized, and it is demonstrated that they outperform model-free algorithms in scenarios with a low evaluation budget. The SBO approach helps practitioners save significant amounts of time and resources in hyperparameter tuning as well as other optimization projects. As a highlight, a novel framework for objectively comparing the efficiency of parallel SBO algorithms is introduced, enabling practitioners to evaluate and select the most effective approach for their specific use case.Based on practical examples, decision support is delivered, detailing which parts of industrial optimization projects can be parallelized and how to prioritize which parts to parallelize first. By following the framework, practitioners can make informed decisions about how to allocate resources and optimize their models efficiently.
Enhancing the Internet with the CONVERGENCE System
by Fernando Almeida Maria Teresa Andrade Nicola Blefari Melazzi Richard Walker Heinrich Hussmann Iakovos S. VenierisConvergence proposes the enhancement of the Internet with a novel, content-centric, publish-subscribe service model based on the versatile digital item (VDI): a common container for all kinds of digital content, including digital representations of real-world resources. VDIs will serve the needs of the future Internet, providing a homogeneous method for handling structured information, incorporating security and privacy mechanisms. CONVERGENCE subsumes the following areas of research: · definition of the VDI as a new fundamental unit of distribution and transaction; · content-centric networking functionality to complement or replace IP-address-based routing; · security and privacy protection mechanisms; · open-source middleware, including a community dictionary service to enable rich semantic searches; · applications, tested under real-life conditions. This book shows how CONVERGENCE allows publishing, searching and subscribing to any content. Creators can publish their content by wrapping it and its descriptions into a VDI, setting rights for other users to access this content, monitor its use, and communicate with people using it; they may even update or revoke content previously published. Access to content is more efficient, as search engines exploit VDI metadata for indexing, and the network uses the content name to ensure users always access the copy closest to them. Every node in the network is a content cache; handover is easy; multicast is natural; peer-to-peer is built-in; time/space-decoupling is possible. Application developers can exploit CONVERGENCE's middleware and network without having to resort to proprietary/ad hoc solutions for common/supporting functionality. Operators can use the network more efficiently, better controlling information transfer and related revenues flows. Network design, operation and management are simplified by integrating diverse functions and avoiding patches and stopgap solutions. Whether as a text for graduate students working on the future of the Internet, or a resource for practitioners providing e-commerce or multimedia services, or scientists defining new technologies, CONVERGENCE will make a valuable contribution to the future shape of the Internet.
Enhancing Undergraduate Learning with Information Technology: A Workshop Summary
by Margaret HiltonEnhancing Undergraduate Learning with Information Technology reports on a meeting of scientists, policy makers, and researchers convened to discuss new approaches to undergraduate science, mathematics, and technology education.The goal of the workshop was to inform workshop participants and the public about issues surrounding the use of information technology in education. To reach this goal, the workshop participants paid particular attention to the following issues: What educational technologies currently exist and how they are being used to transform undergraduate science, engineering, mathematics, and technology education; What is known about the potential future impact of information technology on teaching and learning at the undergraduate level; How to evaluate the impact of information technology on teaching and learning; and What the future might hold.
ENIAC in Action: Making and Remaking the Modern Computer (History of Computing)
by Thomas Haigh Mark Priestley Crispin RopeThe history of the first programmable electronic computer, from its conception, construction, and use to its afterlife as a part of computing folklore.Conceived in 1943, completed in 1945, and decommissioned in 1955, ENIAC (the Electronic Numerical Integrator and Computer) was the first general-purpose programmable electronic computer. But ENIAC was more than just a milestone on the road to the modern computer. During its decade of operational life, ENIAC calculated sines and cosines and tested for statistical outliers, plotted the trajectories of bombs and shells, and ran the first numerical weather simulations. ENIAC in Action tells the whole story for the first time, from ENIAC's design, construction, testing, and use to its afterlife as part of computing folklore. It highlights the complex relationship of ENIAC and its designers to the revolutionary approaches to computer architecture and coding first documented by John von Neumann in 1945.Within this broad sweep, the authors emphasize the crucial but previously neglected years of 1947 to 1948, when ENIAC was reconfigured to run what the authors claim was the first modern computer program to be executed: a simulation of atomic fission for Los Alamos researchers. The authors view ENIAC from diverse perspectives—as a machine of war, as the “first computer,” as a material artifact constantly remade by its users, and as a subject of (contradictory) historical narratives. They integrate the history of the machine and its applications, describing the mathematicians, scientists, and engineers who proposed and designed ENIAC as well as the men—and particularly the women who—built, programmed, and operated it.
ENIAC in Action: Making and Remaking the Modern Computer
by Crispin Rope Mark Priestley Thomas HaighConceived in 1943, completed in 1945, and decommissioned in 1955, ENIAC (the Electronic Numerical Integrator and Computer) was the first general-purpose programmable electronic computer. But ENIAC was more than just a milestone on the road to the modern computer. During its decade of operational life, ENIAC calculated sines and cosines and tested for statistical outliers, plotted the trajectories of bombs and shells, and ran the first numerical weather simulations. ENIAC in Action tells the whole story for the first time, from ENIAC's design, construction, testing, and use to its afterlife as part of computing folklore. It highlights the complex relationship of ENIAC and its designers to the revolutionary approaches to computer architecture and coding first documented by John von Neumann in 1945.Within this broad sweep, the authors emphasize the crucial but previously neglected years of 1947 to 1948, when ENIAC was reconfigured to run what the authors claim was the first modern computer program to be executed: a simulation of atomic fission for Los Alamos researchers. The authors view ENIAC from diverse perspectives -- as a machine of war, as the "first computer," as a material artifact constantly remade by its users, and as a subject of (contradictory) historical narratives. They integrate the history of the machine and its applications, describing the mathematicians, scientists, and engineers who proposed and designed ENIAC as well as the men -- and particularly the women who -- built, programmed, and operated it.
Enjoying Natural Computing: Essays Dedicated to Mario de Jesús Pérez-Jiménez on the Occasion of His 70th Birthday (Lecture Notes in Computer Science #11270)
by Carmen Graciani Agustín Riscos-Núñez Gheorghe Păun Grzegorz Rozenberg Arto SalomaaThis Festschrift is in honor of Mario de Jesús Pérez-Jiménez, Professor in the Department of Computer Science of University of Seville, Spain, on the occasion of his 70th birthday. The title of this volume reflects both his main research area, viz., Natural Computing, and the guiding principle of his functioning: “once you choose to do something, enjoy doing it".The respect that Professor Mario de Jesús Pérez-Jiménez enjoys in the scientific community was well demonstrated by the enthusiastic response received to the request to contribute to this book. The contributions by more than 70 authors from 15 countries cover a wide spectrum of research areas and reflect well the broad range of research interests of Professor Mario de Jesús Pérez-Jiménez. The research areas presented in this Festschrift include membrane computing, spiking neural networks, phylogenetic networks, ant colonies optimization, workbench for biocomputing, reaction systems, entropy of computation, rewriting systems, and insertion-deletion systems.
Enriqueça com o seu telemóvel Android: Ganhe dinheiro com o seu telemóvel Android
by Dave McAllenPare de se impedir de ganhar dinheiro. É impossível estar falido se tiver um dispositivo Android. Cada vez mais pessoas dão por si a reclamar, quer seja contra o governo, as condições de vida, o dinheiro, os rendimentos, os privilégios, a experiência, as habilidades, a falta de emprego ou, por outro lado, a recuperar de tudo isto. Mas, apesar da ascensão sem precedentes, o nosso entendimento da reclamação está aprisionado em raciocínios infundados do século passado, reclamação como um protesto silencioso ou como um meio de obter alguma atenção, e também em estratégias desatualizadas. Desafiando a ideia de tais reclamantes, Dave McAllen oferece uma perspetiva radical e inovadora, argumentando que reclamar da sorte de alguém não é válido na nossa era digital, em que quase todas as pessoas possuem um telefone Android. Ele oferece alguns exemplos daquilo que pode fazer com o seu telefone e ganhar dinheiro e mostra como ver as coisas desta forma pode ajudá-lo a não se desviar do caminho para o sucesso. Fique então a saber porque é que ele diz que os obstáculos para o seu sucesso são você mesmo.
Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases
by Alok Kumar Mayank JainUse ensemble learning techniques and models to improve your machine learning results.Ensemble Learning for AI Developers starts you at the beginning with an historical overview and explains key ensemble techniques and why they are needed. You then will learn how to change training data using bagging, bootstrap aggregating, random forest models, and cross-validation methods. Authors Kumar and Jain provide best practices to guide you in combining models and using tools to boost performance of your machine learning projects. They teach you how to effectively implement ensemble concepts such as stacking and boosting and to utilize popular libraries such as Keras, Scikit Learn, TensorFlow, PyTorch, and Microsoft LightGBM. Tips are presented to apply ensemble learning in different data science problems, including time series data, imaging data, and NLP. Recent advances in ensemble learning are discussed. Sample code is provided in the form of scripts and the IPython notebook.What You Will LearnUnderstand the techniques and methods utilized in ensemble learningUse bagging, stacking, and boosting to improve performance of your machine learning projects by combining models to decrease variance, improve predictions, and reduce biasEnhance your machine learning architecture with ensemble learningWho This Book Is ForData scientists and machine learning engineers keen on exploring ensemble learning
Ensemble Machine Learning: A beginner's guide that combines powerful machine learning algorithms to build optimized models
by Radovan Kavicky Apeksha Jain Ankit DixitKey Features Learn how to maximize popular machine learning algorithms such as random forests, decision trees, AdaBoost, K-nearest neighbor, and more Get a practical approach to building efficient machine learning models using ensemble techniques with real-world use cases Implement concepts such as boosting, bagging, and stacking ensemble methods to improve your model prediction accuracy Book Description Ensembling is a technique of combining two or more similar or dissimilar machine learning algorithms to create a model that delivers superior prediction power. This book will show you how you can use many weak algorithms to make a strong predictive model. This book contains Python code for different machine learning algorithms so that you can easily understand and implement it in your own systems. This book covers different machine learning algorithms that are widely used in the practical world to make predictions and classifications. It addresses different aspects of a prediction framework, such as data pre-processing, model training, validation of the model, and more. You will gain knowledge of different machine learning aspects such as bagging (decision trees and random forests), Boosting (Ada-boost) and stacking (a combination of bagging and boosting algorithms). Then you’ll learn how to implement them by building ensemble models using TensorFlow and Python libraries such as scikit-learn and NumPy. As machine learning touches almost every field of the digital world, you’ll see how these algorithms can be used in different applications such as computer vision, speech recognition, making recommendations, grouping and document classification, fitting regression on data, and more. By the end of this book, you’ll understand how to combine machine learning algorithms to work behind the scenes and reduce challenges and common problems. What you will learn -Understand why bagging improves classification and regression performance -Get to grips with implementing AdaBoost and different variants of this algorithm -See the bootstrap method and its application to bagging -Perform regression on Boston housing data using scikit-learn and NumPy -Know how to use Random forest for IRIS data classification -Get to grips with the classification of sonar dataset using KNN, Perceptron, and Logistic Regression -Discover how to improve prediction accuracy by fine-tuning the model parameters -Master the analysis of a trained predictive model for over-fitting/under-fitting cases
Ensemble Machine Learning: Methods and Applications
by Cha Zhang Yunqian MaIt is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed "ensemble learning" by researchers in computational intelligence and machine learning, it is known to improve a decision system's robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as "boosting" and "random forest" facilitate solutions to key computational issues such as face recognition and are now being applied in areas as diverse as object tracking and bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including the random forest skeleton tracking algorithm in the Xbox Kinect sensor, which bypasses the need for game controllers. At once a solid theoretical study and a practical guide, the volume is a windfall for researchers and practitioners alike.
Ensemble Machine Learning Cookbook: Over 35 practical recipes to explore ensemble machine learning techniques using Python
by Dipayan Sarkar Vijayalakshmi NatarajanThis book is for data scientists, machine learning developers, and deep learning enthusiasts who want to deep dive into machine learning algorithms to build powerful ensemble models. Working knowledge of Python programming and basic statistics is expected.
Ensemble Methods for Machine Learning
by Gautam KunapuliEnsemble machine learning combines the power of multiple machine learning approaches, working together to deliver models that are highly performant and highly accurate.Inside Ensemble Methods for Machine Learning you will find: Methods for classification, regression, and recommendations Sophisticated off-the-shelf ensemble implementations Random forests, boosting, and gradient boosting Feature engineering and ensemble diversity Interpretability and explainability for ensemble methods Ensemble machine learning trains a diverse group of machine learning models to work together, aggregating their output to deliver richer results than a single model. Now in Ensemble Methods for Machine Learning you&’ll discover core ensemble methods that have proven records in both data science competitions and real-world applications. Hands-on case studies show you how each algorithm works in production. By the time you're done, you'll know the benefits, limitations, and practical methods of applying ensemble machine learning to real-world data, and be ready to build more explainable ML systems. About the Technology Automatically compare, contrast, and blend the output from multiple models to squeeze the best results from your data. Ensemble machine learning applies a &“wisdom of crowds&” method that dodges the inaccuracies and limitations of a single model. By basing responses on multiple perspectives, this innovative approach can deliver robust predictions even without massive datasets. About the Book Ensemble Methods for Machine Learning teaches you practical techniques for applying multiple ML approaches simultaneously. Each chapter contains a unique case study that demonstrates a fully functional ensemble method, with examples including medical diagnosis, sentiment analysis, handwriting classification, and more. There&’s no complex math or theory—you&’ll learn in a visuals-first manner, with ample code for easy experimentation! What&’s Inside Bagging, boosting, and gradient boosting Methods for classification, regression, and retrieval Interpretability and explainability for ensemble methods Feature engineering and ensemble diversity About the Reader For Python programmers with machine learning experience. About the Author Gautam Kunapuli has over 15 years of experience in academia and the machine learning industry. Table of Contents PART 1 - THE BASICS OF ENSEMBLES 1 Ensemble methods: Hype or hallelujah? PART 2 - ESSENTIAL ENSEMBLE METHODS 2 Homogeneous parallel ensembles: Bagging and random forests 3 Heterogeneous parallel ensembles: Combining strong learners 4 Sequential ensembles: Adaptive boosting 5 Sequential ensembles: Gradient boosting 6 Sequential ensembles: Newton boosting PART 3 - ENSEMBLES IN THE WILD: ADAPTING ENSEMBLE METHODS TO YOUR DATA 7 Learning with continuous and count labels 8 Learning with categorical features 9 Explaining your ensembles
Ensuring Digital Accessibility through Process and Policy
by Jonathan Lazar Daniel Goldstein Anne TaylorThis book provides readers with a resource to digital accessibility from both a technical and policy perspective.
Ensuring Software Reliability (Quality and Reliability #Vol. 38)
by Ann Marie NeufelderExplains how software reliability can be applied to software programs of all sizes, functions and languages, and businesses. This text provides real-life examples from industries such as defence engineering, and finance. It is aimed at software and quality assurance engineers and graduate students.
Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age
by Institute of MedicineAs digital technologies are expanding the power and reach of research, they are also raising complex issues. These include complications in ensuring the validity of research data; standards that do not keep pace with the high rate of innovation; restrictions on data sharing that reduce the ability of researchers to verify results and build on previous research; and huge increases in the amount of data being generated, creating severe challenges in preserving that data for long-term use. Ensuring the Integrity, Accessibility, and Stewardship of Research Data in the Digital Age examines the consequences of the changes affecting research data with respect to three issues - integrity, accessibility, and stewardship-and finds a need for a new approach to the design and the management of research projects. The report recommends that all researchers receive appropriate training in the management of research data, and calls on researchers to make all research data, methods, and other information underlying results publicly accessible in a timely manner. The book also sees the stewardship of research data as a critical long-term task for the research enterprise and its stakeholders. Individual researchers, research institutions, research sponsors, professional societies, and journals involved in scientific, engineering, and medical research will find this book an essential guide to the principles affecting research data in the digital age.
Ensuring the Integrity of Electronic Health Records: The Best Practices for E-records Compliance
by Orlando LópezData integrity is a critical aspect to the design, implementation, and usage of any system which stores, processes, or retrieves data. The overall intent of any data integrity technique is the same: ensure data is recorded exactly as intended and, upon later retrieval, ensure the data is the same as it was when originally recorded. Any alternation to the data is then traced to the person who made the modification. The integrity of data in a patient’s electronic health record is critical to ensuring the safety of the patient. This book is relevant to production systems and quality control systems associated with the manufacture of pharmaceuticals and medical device products and updates the practical information to enable better understanding of the controls applicable to e-records. The book highlights the e-records suitability implementation and associated risk-assessed controls, and e-records handling. The book also provides updated regulatory standards from global regulatory organizations such as MHRA, Medicines and Healthcare Products Regulatory Agency (UK); FDA, Food and Drug Administration (US); National Medical Products Association (China); TGA, Therapeutic Goods Administration (Australia); SIMGP, Russia State Institute of Medicines and Good Practices; and the World Health Organization, to name a few.
Entanglement in Spin Chains: From Theory to Quantum Technology Applications (Quantum Science and Technology)
by Abolfazl Bayat Sougato Bose Henrik JohannessonThis book covers recent developments in the understanding, quantification, and exploitation of entanglement in spin chain models from both condensed matter and quantum information perspectives. Spin chain models are at the foundation of condensed matter physics and quantum information technologies and elucidate many fundamental phenomena such as information scrambling, quantum phase transitions, and many-body localization. Moreover, many quantum materials and emerging quantum devices are well described by spin chains. Comprising accessible, self-contained chapters written by leading researchers, this book is essential reading for graduate students and researchers in quantum materials and quantum information. The coverage is comprehensive, from the fundamental entanglement aspects of quantum criticality, non-equilibrium dynamics, classical and quantum simulation of spin chains through to their experimental realizations, and beyond into machine learning applications.
Enter The World Of Computers: Based on Windows 10 and MS Office 2016 class 1
by Kartikey KumarEnter The World Of Computers, for classes 1 to 8, based on NEP 2020 guidelines, introduces primary and middle school students to the world of Computers and Information Technology in a carefully graded manner. It helps the students see computer as their friend, so that they not only understand but also use it with ease and to their advantage.
Enterprise 2.0: Social Networking Tools to Transform Your Organization
by Jessica KeyesEnterprise 2.0 (E 2.0) has caught the collective imagination of executives who are innovating to radically change the face of business. E 2.0 takes full benefit of social networking, including blogs, discussion boards, mashups, and all that is sharable and combinable.Examining organizations and their social activities, Enterprise 2.0: Social N
Enterprise Agility: Being Agile in a Changing World
by Sunil MundraEnterprise Agility is practical framework for enhancing Agility and equipping your company with the tools to survive. Key Features● Prepare your company to navigate the rapidly-moving business world● Enhance Agility in every component of your organization● Build a framework that meets the unique requirements of your enterpriseBook DescriptionThe biggest challenge enterprises face today is dealing with fast-paced change in all spheres of business. Enterprise Agility shows how an enterprise can address this challenge head on and thrive in the dynamic environment. Avoiding the mechanistic construction of existing enterprises that focus on predictability and certainty, Enterprise Agility delivers practical advice for responding and adapting to the scale and accelerating pace of disruptive change in the business environment.Agility is a fundamental shift in thinking about how enterprises work to effectively deal with disruptive changes in the business environment. The core belief underlying agility is that enterprises are open and living systems. These living systems, also known as complex adaptive systems (CAS), are ideally suited to deal with change very effectively.Agility is to enterprises what health is to humans. There are some foundational principles that can be broadly applied, but the definition of healthy is very specific to each individual. Enterprise Agility takes a similar approach with regard to agility: it suggests foundational practices to improve the overall health of the body—culture, mindset, and leadership—and the health of its various organs: people, process, governance, structure, technology, and customers. The book also suggests a practical framework to create a plan to enhance agility.What you will learnDrive agility-oriented change across the enterpriseUnderstand why agility matters (more than ever) to modern enterprises Adopt and influence an Agile mindset in your teams and in your organization Understand the concept of a CAS and how to model enterprise and leadership behaviors on CAS characteristics to enhance enterprise agility Understand and convey the differences between Agile and true enterprise agility Create an enterprise-specific action plan to enhance agility Become a champion for enterprise agilityRecognize the advantages and challenges of distributed teams, and how Agile ways of working can remedy the rough spotsEnable and motivate your IT partners to adopt Agile ways of workingWho this book is forEnterprise Agility is a tool for anyone with the motivation to influence outcomes in an enterprise, who aspires to improve Agility. Readers from the following backgrounds will benefit: chief executive officer, chief information officer, people/human resource director, information technology director, head of change program, head of transformation, and Agile coach/consultant.
Enterprise AI For Dummies
by Zachary JarvinenMaster the application of artificial intelligence in your enterprise with the book series trusted by millions In Enterprise AI For Dummies, author Zachary Jarvinen simplifies and explains to readers the complicated world of artificial intelligence for business. Using practical examples, concrete applications, and straightforward prose, the author breaks down the fundamental and advanced topics that form the core of business AI. Written for executives, managers, employees, consultants, and students with an interest in the business applications of artificial intelligence, Enterprise AI For Dummies demystifies the sometimes confusing topic of artificial intelligence. No longer will you lag behind your colleagues and friends when discussing the benefits of AI and business. The book includes discussions of AI applications, including : · Streamlining business operations · Improving decision making · Increasing automation · Maximizing revenue The For Dummies series makes topics understandable, and as such, this book is written in an easily understood style that’s perfect for anyone who seeks an introduction to a usually unforgiving topic.