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Up and Running with DAX for Power BI
Up and Running with DAX for Power BI

Take a concise approach to learning how DAX, the function language of Power BI and PowerPivot, works. This book focuses on explaining the core concepts of DAX so that ordinary folks can gain the skills required to tackle complex data analysis problems. But make no mistake, this is in no way an introductory book on DAX. A number of the topics you will learn, such as the concepts of context transition and table expansion, are considered advanced and challenging areas of DAX. While there are numerous resources on DAX, most are written with developers in mind, making learning DAX appear an overwhelming challenge, especially for those who are coming from an Excel background or with limited coding experience. The reality is, to hit the ground running with DAX, it's not necessary to wade through copious pages on rarified DAX functions and the technical aspects of the language. There are just a few mandatory concepts that must be fully understood before DAX can be mastered. Knowledge of eve ...
Artificial Intelligence in Medical Sciences and Psychology
Artificial Intelligence in Medical Sciences and Psychology

Get started with artificial intelligence for medical sciences and psychology. This book will help healthcare professionals and technologists solve problems using machine learning methods, computer vision, and natural language processing (NLP) techniques. The book covers ways to use neural networks to classify patients with diseases. You will know how to apply computer vision techniques and convolutional neural networks (CNNs) to segment diseases such as cancer (e.g., skin, breast, and brain cancer) and pneumonia. The hidden Markov decision making process is presented to help you identify hidden states of time-dependent data. In addition, it shows how NLP techniques are used in medical records classification. This book is suitable for experienced practitioners in varying medical specialties (neurology, virology, radiology, oncology, and more) who want to learn Python programming to help them work efficiently. It is also intended for data scientists, machine learning engineers, m ...
A Complete Guide to Docker for Operations and Development
A Complete Guide to Docker for Operations and Development

Harness the power of Docker by containerizing your code with all its libraries and file systems to consistently run anywhere. This book is your source for learning all about Docker operations and development. It's divided into two units and focuses on the topics that the Docker Certified Associate exam covers. Unit 1 covers the Docker fundamentals, such as Docker Enterprise for Operations, Docker Enterprise for Developers, Swarm, and an introduction to Kubernetes. You will learn how to install Docker Community Edition, Docker Enterprise Edition with Kubernetes and CLI. Also, you will learn the Docker cycle, container lifecycle, develop applications in any language, wrap, build, ship, and deploy them for production. Finally, you will learn how to create a Swarm cluster, deploy an app to it, and manage it with the best practices according to the current technologies. Unit 2 provides quizzes to help you prepare for the certification test. The DCA exam format and the question style h ...
Advanced Analytics and Deep Learning Models
Advanced Analytics and Deep Learning Models

The book provides readers with an in-depth understanding of concepts and technologies related to the importance of analytics and deep learning in many useful real-world applications such as e-healthcare, transportation, agriculture, stock market, etc. Advanced analytics is a mixture of machine learning, artificial intelligence, graphs, text mining, data mining, semantic analysis. It is an approach to data analysis. Beyond the traditional business intelligence, it is a semi and autonomous analysis of data by using different techniques and tools. However, deep learning and data analysis both are high centers of data science. Almost all the private and public organizations collect heavy amounts of data, i.e., domain-specific data. Many small/large companies are exploring large amounts of data for existing and future technology. Deep learning is also exploring large amounts of unsupervised data making it beneficial and effective for big data. Deep learning can be used to deal with al ...
A Network Architect's Guide to 5G
A Network Architect's Guide to 5G

As 5G transforms mobile usage and services, network professionals will need to significantly evolve their transport network architectures towards greater sophistication and stronger integration with radio networks, and facilitate transition towards cloud-native 5G mobile core. Until now, however, most 5G guides have foregrounded RF/radio and mobile core innovations, not its implications for data networks. A Network Architects Guide to 5G fills the gap, giving network architects, designers, and engineers essential knowledge for designing and planning their own 5G networks. Drawing on decades of experience with global service providers and enterprise networks, the authors illuminate new and evolving network technologies necessary for building 5G-capable networks, such as segment routing, network slicing, timing and synchronization, edge computing, distributed data centers, integration with public cloud, and more. They explain how 5G blurs boundaries between mobile core, radio access, ...
Time Series Analysis with Python Cookbook
Time Series Analysis with Python Cookbook

Time series data is everywhere, available at a high frequency and volume. It is complex and can contain noise, irregularities, and multiple patterns, making it crucial to be well-versed with the techniques covered in this book for data preparation, analysis, and forecasting. This book covers practical techniques for working with time series data, starting with ingesting time series data from various sources and formats, whether in private cloud storage, relational databases, non-relational databases, or specialized time series databases such as InfluxDB. Next, you'll learn strategies for handling missing data, dealing with time zones and custom business days, and detecting anomalies using intuitive statistical methods, followed by more advanced unsupervised ML models. The book will also explore forecasting using classical statistical models such as Holt-Winters, SARIMA, and VAR. The recipes will present practical techniques for handling non-stationary data, using power transforms, A ...
Adobe Illustrator for Creative Professionals
Adobe Illustrator for Creative Professionals

Adobe Illustrator is a vector-based art tool for visual creatives. It is an industry-standard tool that helps you take a design from concept to completion, including the process of peer collaboration and client feedback. Complete with step-by-step explanations of essential concepts and practical examples, you'll begin to build confidence as you master the methods of successful illustrators in the industry by exploring crucial tools and techniques of Adobe Illustrator. You'll learn how to create objects using different tools and methods while assigning varied attributes and appearances. Throughout the book, you'll strengthen your skills in developing structures for maintaining organization as your illustration grows. By the end of this Adobe Illustrator book, you'll have gained the confidence you need to not only create content in the desired format and for the right audience but also build eye-catching vector art based on solid design principles. ...
Algorithms for Decision Making
Algorithms for Decision Making

A broad introduction to algorithms for decision making under uncertainty, introducing the underlying mathematical problem formulations and the algorithms for solving them. Automated decision-making systems or decision-support systems - used in applications that range from aircraft collision avoidance to breast cancer screening - must be designed to account for various sources of uncertainty while carefully balancing multiple objectives. This textbook provides a broad introduction to algorithms for decision making under uncertainty, covering the underlying mathematical problem formulations and the algorithms for solving them. The book first addresses the problem of reasoning about uncertainty and objectives in simple decisions at a single point in time, and then turns to sequential decision problems in stochastic environments where the outcomes of our actions are uncertain. It goes on to address model uncertainty, when we do not start with a known model and must learn how to act t ...
Blazor Succinctly
Blazor Succinctly

Blazor technology enables you to create sophisticated, manageable, and extensible single-page applications using C# and Razor syntax. Blazor Succinctly will cover the core elements of Blazor, then explore additional features by building a sample help desk application. Michael Washington will take readers from creating the project in Visual Studio to implementing email notifications. ...
Data Protection for the Hybrid Cloud
Data Protection for the Hybrid Cloud

If you are responsible for architecting and designing the backup strategy for your organization, especially if you're looking for ways to incorporate cloud backup into your business continuity scenarios, this book is for you. With the increasing trends in virtualization as well as the move to the pubic cloud, IT organizations are headed toward a world where data and applications run in on-premises private clouds as well as in the public cloud. This has key implications for data protection strategy, and it is important to choose the solution that provides the same level of data protection you have afforded so far while allowing you to harness the power of the public cloud. We will cover how the Azure Backup service has evolved into a first-class platform-as-a-service (PaaS) service in Microsoft Azure that integrates with the on-premises enterprise class backup product, System Center Data Protection Manager (DPM), to provide a seamless hybrid cloud backup solution. Current backup prod ...
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