Artificial Intelligence - AI Innovations for Data Centers - Professional's Guide

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Practical AI for Business Leaders, Product Managers, and Entrepreneurs

Brief

Book

Implementing advanced analytics at scale in a competitive landscape requires the speed, agility, and mindset of an entrepreneur. It is here that organizations in the future will gain an edge. This book provides the practical guidance　 and theoretical background necessary to implement advanced analytics in mid- to large organizations. The theoretical component draws from the best academic research in management science, computer science, and behavioral economics. The practical component provides design patterns and case studies for implementing big data at scale in complex organizations. The design patterns take the mindset of an entrepreneur having to execute with speed and agility against the backdrop of business, technical, and stakeholder complexity.

Demystifying Azure AI...Implementing the Right Features

Brief

Book

Explore artificial intelligence offerings by Microsoft Azure, along with its other services. This book will help you implement AI features in various Azure services to help build your organization and customers. The book starts by introducing you to the Azure Cognitive Search service to create and use an application. You then will learn the built-in automatic tuning intelligence mechanism in Azure SQL Database. This is an important feature you can use to enable Azure SQL Database to optimize the performance of your queries. Next, you will go through AI services with Azure Integration Platform service and Azure Logic Apps to build a modern intelligent workflow in your application. Azure functions are discussed as a part of its server-less feature. The book concludes by teaching you how to work with Power Automate to analyze your business workflow. After reading this book, you will be able to understand and work with different Azure Cognitive Services in AI.

On the path to AI... foundations of the machine learning age

Brief

Book

This open access book explores machine learning and its impact on how we make sense of the world. It does so by bringing together two ‘revolutions’ in a surprising analogy: the revolution of machine learning, which has placed computing on the path to artificial intelligence, and the revolution in thinking about the law that was spurred by Oliver Wendell Holmes Jr in the last two decades of the 19th century. Holmes reconceived law as prophecy based on experience, prefiguring the buzzwords of the machine learning age―prediction based on datasets. On the path to AI introduces readers to the key concepts of machine learning, discusses the potential applications and limitations of predictions generated by machines using data, and informs current debates amongst scholars, lawyers and policy makers on how it should be used and regulated wisely. Technologists will also find useful lessons learned from the last 120 years of legal grappling with accountability, and biased data.

Artificial Intelligence and Machine Learning for Digital Pathology...

Brief

Book

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support. Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

Graph Neural Networks...Artificial Intelligence and Machine Learning

Brief

Book

Nodes in graphs usually contain useful feature information that cannot be well addressed in most unsupervised representation learning methods (e.g., network embedding methods). Graph neural networks (GNNs) are proposed to combine the feature information and the graph structure to learn better representations on graphs via feature propagation and aggregation. Due to its convincing performance and high interpretability, GNN has recently become a widely applied graph analysis tool.  This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introduced such as graph convolutional networks, graph recurrent networks, graph attention networks, graph residual networks, and several general frameworks. Variants for different graph types and advanced training methods are also included. As for the applications of GNNs, the book categorizes them into structural, non-structural, and other scenarios, and then it introduces several typical models on solving these tasks. Finally, the closing chapters provide GNN open resources and the outlook of several future directions.

Federated Learning...Synthesis Lectures on #AI and #ML

Book

Brief

Traditional machine learning approaches need to combine all data at one location, typically a data center, which may very well violate the laws on user privacy and data confidentiality. Today, many parts of the world demand that technology companies treat user data carefully according to user-privacy laws. The European Union's General Data Protection Regulation (GDPR) is a prime example. In this book, we describe how federated machine learning addresses this problem with novel solutions combining distributed machine learning, cryptography and security, and incentive mechanism design based on economic principles and game theory. We explain different types of privacy-preserving machine learning solutions and their technological backgrounds, and highlight some representative practical use cases. We show how federated learning can become the foundation of next-generation machine learning that caters to technological and societal needs for responsible AI development and application.

Machine Learning and Artificial Intelligence with Just Enough R!

Brief

Book

Features Gets you quickly using R as a problem-solving tool Uses RStudio’s integrated development environment  Shows how to interface R with SQLite  Includes examples using R’s Rattle graphical user interface  Requires no prior knowledge of R, machine learning, or computer programming Offers over 50 scripts written in R, including several problem-solving templates that, with slight modification, can be used again and again  Covers the most popular machine learning techniques, including ensemble-based methods and logistic regression  Includes end-of-chapter exercises, many of which can be solved by modifying existing scripts  Includes datasets from several areas, including business, health and medicine, and science

Artificial Intelligence & Data Science..2 in 1

Book

Brief

Discover why learning as much as you can about AI, data science, and machine learning is worth the time and effort with this easy-to-understand guide designed for beginners but is chockful of information even more experienced people can use. This two-book bundle offers a glimpse into these fascinating topics that will carry you through the 21st century and help you to analyze or scale your business or practices. Leave the guessing to someone else and finally get a full grasp of the information you need to move up in the business world, understand your business records and/or data better, and gain insight into the world of robotics. This two-book bundle has all the answers you need to get your foot in the door and to prepare you for what lies ahead in the world of technology.

Lean AI...How Innovative Startups Use Artificial Intelligence

Brief

Book

How can startups successfully scale customer acquisition and revenue growth with a Lean team? Out-of-the-box acquisition solutions from Facebook, Google, and others provide a good start, but the companies that can tailor those solutions to meet their specific needs, objectives, and goals will come out winners. But that hasn’t been an easy task—until now. With this practical book, the author shows you how to use AI and automation to provide an operational layer atop those acquisition solutions to deliver amazing results for your company.

Implications of Artificial Intelligence for Cybersecurity...

Brief

Book

In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity.

Artificial Intelligence And LegalTech Essentials...

Brief	Book
A vital book by industry thought leader and global AI expert, Dr. Lance Eliot, and based on his popular AI Insider series and podcasts, this fascinating book provides pioneering advances for the field of AI and law. Included too are keen insights about the practical application of Artificial Intelligence (AI) and Machines Learning (ML) in LegalTech and LawTech.

Artificial Intelligence and Machine Learning for Digital Pathology...

Brief

Book

Data driven Artificial Intelligence (AI) and Machine Learning (ML) in digital pathology, radiology, and dermatology is very promising. In specific cases, for example, Deep Learning (DL), even exceeding human performance. However, in the context of medicine it is important for a human expert to verify the outcome. Consequently, there is a need for transparency and re-traceability of state-of-the-art solutions to make them usable for ethical responsible medical decision support.  Moreover, big data is required for training, covering a wide spectrum of a variety of human diseases in different organ systems. These data sets must meet top-quality and regulatory criteria and must be well annotated for ML at patient-, sample-, and image-level. Here biobanks play a central and future role in providing large collections of high-quality, well-annotated samples and data. The main challenges are finding biobanks containing ‘‘fit-for-purpose’’ samples, providing quality related meta-data, gaining access to standardized medical data and annotations, and mass scanning of whole slides including efficient data management solutions.

Artificial Intelligence...A Modern Approach

Brief

Book

The long-anticipated revision of Artificial Intelligence: A Modern Approach explores the full breadth and depth of the field of artificial intelligence (AI). The 3rd Edition brings readers on the technologies, presents concepts in a more unified manner, and offers new or expanded coverage of machine learning, deep learning, transfer learning, multiagent systems, robotics, natural language processing, causality, probabilistic programming, privacy, fairness, and safe AI.

The Human Cloud...How Today's Changemakers Use Artificial Intelligence

Brief

Book

By replacing fear with knowledge, you will better understand how this shift in employment is a good thing, be equipped to embrace the positive advantages new technology brings and use it all to your benefit, and further secure how your own job is shaped so you are never left behind. Topics unpacked in The Human Cloud include: How employees and employers will be able to take advantage of the new automated and freelance-based workplace. How they will be able to take advantage of the new technology disruptions the machine cloud will create.  Why the changes employees and employers are seeing aren’t the projection of doom that many are predicting; they can actually create many new career opportunities. How to navigate the coming job marketplace.

Artificial Intelligence for Business...A Roadmap

Brief

Book

This masterpiece will provide the reader with an easy to understand roadmap for how to take an organization through the adoption of AI technology. It will first help with the identification of which business problems and opportunities are right for AI and how to prioritize them to maximize the likelihood of success. Specific methodologies are introduced to help with finding critical training data within an organization and how to fill data gaps if they exist. With data in hand, a scoped prototype can be built to limit risk and provide tangible value to the organization as a whole to justify further investment. Finally, a production level AI system can be developed with best practices to ensure quality with not only the application code, but also the AI models. Finally, with this particular AI adoption journey at an end, the authors will show that there is additional value to be gained by iterating on this AI adoption lifecycle and improving other parts of the organization.

E

Artificial Intelligence for Learning..to Support Employee Development

Brief

Book

The book debunks the myths and cuts through the hype around AI allowing L&D practitioners to feel confident in their ability to critically assess where artificial intelligence can make a measurable difference and where it is worth investing in. There is also critical discussion of how AI is an aid to learning and development, not a replacement as well as how it can be used to boost the effectiveness of workplace learning, reduce drop off rates in online learning and improve ROI. With real-world examples from companies who have effectively implemented AI and seen the benefits as well as case studies from organizations including Netflix, British Airways and the NHS, this book is essential reading for all L&D practitioners needing to understand AI and what it means in practice.

Cyber Minds...across the cloud, data, artificial intelligence, blockchain...

Brief

Book

With new technology threats, rising international tensions, and state-sponsored cyber attacks, cybersecurity is more important than ever. Cyber Minds serves as a strategic briefing on cybersecurity and data safety, collecting expert insights from sector security leaders. Businesses and states depend on effective cybersecurity. This book will help you to arm and inform yourself on what you need to know to keep your business – or your country – safe.

Applied Artificial Intelligence...A Handbook For Business Leaders

Brief

Book

Applied Artificial Intelligence is a practical guide for business leaders who are passionate about leveraging machine intelligence to enhance the productivity of their organizations and the quality of life in their communities. If you want to drive innovation by combining data, technology, design, and people to solve real problems at an enterprise scale, this is your playbook. This book does not overload you with details on debugging TensorFlow code nor bore you with generalizations about the future of humanity. Instead, we teach you how to lead successful AI initiatives by prioritizing the right opportunities, building a diverse team of experts, conducting strategic experiments, and consciously designing your solutions to benefit both your organization and society as a whole. This book is focused on helping you drive concrete business decisions through applications of artificial intelligence and machine learning. Written with the combined knowledge of three experts in the field, Applied Artificial Intelligence is the best practical guide for business leaders looking to get true value from the adoption of machine learning technology.

Machine Learning and Artificial Intelligence...

Brief

Book

This book provides comprehensive coverage of combined Artificial Intelligence (AI) and Machine Learning (ML) theory and applications. Rather than looking at the field from only a theoretical or only a practical perspective, this book unifies both perspectives to give holistic understanding. The first part introduces the concepts of AI and ML and their origin and current state. The second and third parts delve into conceptual and theoretic aspects of static and dynamic ML techniques. The forth part describes the practical applications where presented techniques can be applied. The fifth part introduces the user to some of the implementation strategies for solving real life ML problems. The book is appropriate for students in graduate and upper undergraduate courses in addition to researchers and professionals. It makes minimal use of mathematics to make the topics more intuitive and accessible.