Advanced Analytics with Transact-SQL
Learn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration. No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and surviva ...
Learn about business intelligence (BI) features in T-SQL and how they can help you with data science and analytics efforts without the need to bring in other languages such as R and Python. This book shows you how to compute statistical measures using your existing skills in T-SQL. You will learn how to calculate descriptive statistics, including centers, spreads, skewness, and kurtosis of distributions. You will also learn to find associations between pairs of variables, including calculating linear regression formulas and confidence levels with definite integration. No analysis is good without data quality. Advanced Analytics with Transact-SQL introduces data quality issues and shows you how to check for completeness and accuracy, and measure improvements in data quality over time. The book also explains how to optimize queries involving temporal data, such as when you search for overlapping intervals. More advanced time-oriented information in the book includes hazard and surviva ...
Data Engineering on Azure
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. 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. 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, p ...
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. 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. 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, p ...
Practical Weak Supervision
Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process; Use Snorkel AI for weak supervision and data programming; Get code examples for using Snorkel to label text and image datasets; Use a weakly labeled dataset f ...
Most data scientists and engineers today rely on quality labeled data to train machine learning models. But building a training set manually is time-consuming and expensive, leaving many companies with unfinished ML projects. There's a more practical approach. In this book, Wee Hyong Tok, Amit Bahree, and Senja Filipi show you how to create products using weakly supervised learning models. You'll learn how to build natural language processing and computer vision projects using weakly labeled datasets from Snorkel, a spin-off from the Stanford AI Lab. Because so many companies have pursued ML projects that never go beyond their labs, this book also provides a guide on how to ship the deep learning models you build. Get up to speed on the field of weak supervision, including ways to use it as part of the data science process; Use Snorkel AI for weak supervision and data programming; Get code examples for using Snorkel to label text and image datasets; Use a weakly labeled dataset f ...
Conversational AI
Conversational AI: Chatbots that work teaches you to create the kind of AI-enabled assistants that are revolutionizing the customer service industry. You'll learn to build effective conversational AI that can automate common inquiries and easily address your customers' most common problems. This engaging and entertaining book delivers the essential technical and creative skills for designing successful AI solutions, from coding process flows and training machine learning, to improving your written dialog. Create AI-driven chatbots and other intelligent agents that humans actually enjoy talking to! Adding intelligence to automated response systems saves time and money for you and your customers. Conversational AI systems excel at routine tasks such as answering common questions, classifying issues, and routing customers to the appropriate human staff. This book will show you how to build effective, production-ready AI assistants. Conversational AI is a guide to creating AI-driven ...
Conversational AI: Chatbots that work teaches you to create the kind of AI-enabled assistants that are revolutionizing the customer service industry. You'll learn to build effective conversational AI that can automate common inquiries and easily address your customers' most common problems. This engaging and entertaining book delivers the essential technical and creative skills for designing successful AI solutions, from coding process flows and training machine learning, to improving your written dialog. Create AI-driven chatbots and other intelligent agents that humans actually enjoy talking to! Adding intelligence to automated response systems saves time and money for you and your customers. Conversational AI systems excel at routine tasks such as answering common questions, classifying issues, and routing customers to the appropriate human staff. This book will show you how to build effective, production-ready AI assistants. Conversational AI is a guide to creating AI-driven ...
Event- and Data-Centric Enterprise Risk-Adjusted Return Management
Take a holistic view of enterprise risk-adjusted return management in banking. This book recommends that a bank transform its siloed operating model into an agile enterprise model. It offers an event-driven, process-based, data-centric approach to help banks plan and implement an enterprise risk-adjusted return model (ERRM), keeping the focus on business events, processes, and a loosely coupled enterprise service architecture. Most banks suffer from a lack of good quality data for risk-adjusted return management. This book provides an enterprise data management methodology that improves data quality by defining and using data ontology and taxonomy. It extends the data narrative with an explanation of the characteristics of risk data, the usage of machine learning, and provides an enterprise knowledge management methodology for risk-return optimization. The book provides numerous examples for process automation, data analytics, event management, knowledge management, and improvements ...
Take a holistic view of enterprise risk-adjusted return management in banking. This book recommends that a bank transform its siloed operating model into an agile enterprise model. It offers an event-driven, process-based, data-centric approach to help banks plan and implement an enterprise risk-adjusted return model (ERRM), keeping the focus on business events, processes, and a loosely coupled enterprise service architecture. Most banks suffer from a lack of good quality data for risk-adjusted return management. This book provides an enterprise data management methodology that improves data quality by defining and using data ontology and taxonomy. It extends the data narrative with an explanation of the characteristics of risk data, the usage of machine learning, and provides an enterprise knowledge management methodology for risk-return optimization. The book provides numerous examples for process automation, data analytics, event management, knowledge management, and improvements ...
HackSpace Magazine: Issue 50
Machine learning used to be the preserve of university research departments with money to burn on high-power, high-cost kit - but not any more! Thanks to a new breed of affordable dev boards, anyone can get in on the act at pocket money prices. We've trawled the makersphere for the best, most creative machine learning projects to show just what can be done. The future of machine learning is awesome - and it's here right now! - Light painting: incredible images created with a Raspberry Pi, LEDs, and the passage of time - Matt Stultz: 3D printing guru on Prusa, printing and the pandemic - Lathe gearbox: use a Raspberry Pi Pico to control the speed of a spinny thing - Christmas PCBs: get into the festive mood with custom flashing decorations ...
Machine learning used to be the preserve of university research departments with money to burn on high-power, high-cost kit - but not any more! Thanks to a new breed of affordable dev boards, anyone can get in on the act at pocket money prices. We've trawled the makersphere for the best, most creative machine learning projects to show just what can be done. The future of machine learning is awesome - and it's here right now! - Light painting: incredible images created with a Raspberry Pi, LEDs, and the passage of time - Matt Stultz: 3D printing guru on Prusa, printing and the pandemic - Lathe gearbox: use a Raspberry Pi Pico to control the speed of a spinny thing - Christmas PCBs: get into the festive mood with custom flashing decorations ...
Natural Language Processing Projects
Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentenc ...
Leverage machine learning and deep learning techniques to build fully-fledged natural language processing (NLP) projects. Projects throughout this book grow in complexity and showcase methodologies, optimizing tips, and tricks to solve various business problems. You will use modern Python libraries and algorithms to build end-to-end NLP projects. The book starts with an overview of natural language processing (NLP) and artificial intelligence to provide a quick refresher on algorithms. Next, it covers end-to-end NLP projects beginning with traditional algorithms and projects such as customer review sentiment and emotion detection, topic modeling, and document clustering. From there, it delves into e-commerce related projects such as product categorization using the description of the product, a search engine to retrieve the relevant content, and a content-based recommendation system to enhance user experience. Moving forward, it explains how to build systems to find similar sentenc ...
MLOps Engineering at Scale
MLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You'll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities. A production-ready machine learning system includes efficient data pipelines, integrated monitoring, and means to scale up and down based on demand. Using cloud-based services to implement ML infrastructure reduces development time and lowers hosting costs. Serverless MLOps eliminates the need to build and maintain custom infrastructure, so you can concentrate on your data, models, and algorithms. MLOps Engineering at Scale teaches you how to implement efficient machine learning systems usi ...
MLOps Engineering at Scale shows you how to put machine learning into production efficiently by using pre-built services from AWS and other cloud vendors. You'll learn how to rapidly create flexible and scalable machine learning systems without laboring over time-consuming operational tasks or taking on the costly overhead of physical hardware. Following a real-world use case for calculating taxi fares, you will engineer an MLOps pipeline for a PyTorch model using AWS server-less capabilities. A production-ready machine learning system includes efficient data pipelines, integrated monitoring, and means to scale up and down based on demand. Using cloud-based services to implement ML infrastructure reduces development time and lowers hosting costs. Serverless MLOps eliminates the need to build and maintain custom infrastructure, so you can concentrate on your data, models, and algorithms. MLOps Engineering at Scale teaches you how to implement efficient machine learning systems usi ...
Software Architecture with C# 10 and .NET 6, 3rd Edition
Software architecture is the practice of implementing structures and systems that streamline the software development process and improve the quality of an app. This fully revised and expanded third edition, featuring the latest features of .NET 6 and C# 10, enables you to acquire the key skills, knowledge, and best practices required to become an effective software architect. Software Architecture with C# 10 and .NET 6, Third Edition features new chapters that describe the importance of the software architect, microservices with ASP.NET Core, and analyzing the architectural aspects of the front-end in the applications, including the new approach of .NET MAUI. It also includes a new chapter focused on providing a short introduction to artificial intelligence and machine learning using ML.NET, and updated chapters on Azure Kubernetes Service, EF Core, and Blazor. You will begin by understanding how to transform user requirements into architectural needs and exploring the differenc ...
Software architecture is the practice of implementing structures and systems that streamline the software development process and improve the quality of an app. This fully revised and expanded third edition, featuring the latest features of .NET 6 and C# 10, enables you to acquire the key skills, knowledge, and best practices required to become an effective software architect. Software Architecture with C# 10 and .NET 6, Third Edition features new chapters that describe the importance of the software architect, microservices with ASP.NET Core, and analyzing the architectural aspects of the front-end in the applications, including the new approach of .NET MAUI. It also includes a new chapter focused on providing a short introduction to artificial intelligence and machine learning using ML.NET, and updated chapters on Azure Kubernetes Service, EF Core, and Blazor. You will begin by understanding how to transform user requirements into architectural needs and exploring the differenc ...
Pro iPhone Development with SwiftUI, 3rd Edition
You know the basics. Your Swift code flows with logic and ease. This isn't your first time building a workable app for iOS platforms. Now, it's time to build a magical app for iOS platforms! Move beyond what you mastered in the best-selling Beginning iPhone Development with SwiftUI. Debug Swift code, use multi-threaded programming with Grand Central Dispatch, pass data between view controllers, and design apps functional in multiple languages. Not only will your apps run like magic under the hood but, with the new standard of SwiftUI, you'll add animations, scaling, multiscreen support, and so much more to your interfaces. You'll also see how to integrate audio and video files in your apps, access the camera and send pictures to and from the Photos library, use location services to pinpoint your user's position on a map, and display web pages in-app. Don't just stop at flawless code and stickily engaging interfaces. Give your apps a mind with Apple's advanced frameworks for machine ...
You know the basics. Your Swift code flows with logic and ease. This isn't your first time building a workable app for iOS platforms. Now, it's time to build a magical app for iOS platforms! Move beyond what you mastered in the best-selling Beginning iPhone Development with SwiftUI. Debug Swift code, use multi-threaded programming with Grand Central Dispatch, pass data between view controllers, and design apps functional in multiple languages. Not only will your apps run like magic under the hood but, with the new standard of SwiftUI, you'll add animations, scaling, multiscreen support, and so much more to your interfaces. You'll also see how to integrate audio and video files in your apps, access the camera and send pictures to and from the Photos library, use location services to pinpoint your user's position on a map, and display web pages in-app. Don't just stop at flawless code and stickily engaging interfaces. Give your apps a mind with Apple's advanced frameworks for machine ...