Practical Data Science
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. Become fluent in the essential concepts and terminology of data science and data engineering; Build and use a technology stack that meets industry criteria; Master the methods for retrieving actionable business knowledge; Coordinate the handling of polyglot data types in a data lake for repeatable results. ...
Learn how to build a data science technology stack and perform good data science with repeatable methods. You will learn how to turn data lakes into business assets. The data science technology stack demonstrated in Practical Data Science is built from components in general use in the industry. Data scientist Andreas Vermeulen demonstrates in detail how to build and provision a technology stack to yield repeatable results. He shows you how to apply practical methods to extract actionable business knowledge from data lakes consisting of data from a polyglot of data types and dimensions. Become fluent in the essential concepts and terminology of data science and data engineering; Build and use a technology stack that meets industry criteria; Master the methods for retrieving actionable business knowledge; Coordinate the handling of polyglot data types in a data lake for repeatable results. ...
PostgreSQL: Up and Running, 2nd Edition
Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.2, 9.3, and 9.4, you'll also discover that PostgeSQL is more than a database system - it's also an impressive application platform. With examples throughout, this book shows you how to achieve tasks that are difficult or impossible in other databases. This second edition covers LATERAL queries, augmented JSON support, materialized views, and other key topics. If you're a current PostgreSQL user, you'll pick up gems you may have missed before. ...
Thinking of migrating to PostgreSQL? This clear, fast-paced introduction helps you understand and use this open source database system. Not only will you learn about the enterprise class features in versions 9.2, 9.3, and 9.4, you'll also discover that PostgeSQL is more than a database system - it's also an impressive application platform. With examples throughout, this book shows you how to achieve tasks that are difficult or impossible in other databases. This second edition covers LATERAL queries, augmented JSON support, materialized views, and other key topics. If you're a current PostgreSQL user, you'll pick up gems you may have missed before. ...
C# 7 and .NET: Designing Modern Cross-platform Applications
C# is a widely used programming language, thanks to its easy learning curve, versatility, and support for modern paradigms. The language is used to create desktop apps, background services, web apps, and mobile apps. .NET Core is open source and compatible with Mac OS and Linux. There is no limit to what you can achieve with C# and .NET Core. This Learning Path begins with the basics of C# and object-oriented programming (OOP) and explores features of C#, such as tuples, pattern matching, and out variables. You will understand.NET Standard 2.0 class libraries and ASP.NET Core 2.0, and create professional websites, services, and applications. You will become familiar with mobile app development using Xamarin.Forms and learn to develop high-performing applications by writing optimized code with various profiling techniques. By the end of C# 7 and .NET: Designing Modern Cross-platform Applications, you will have all the knowledge required to build modern, cross-platform apps using C ...
C# is a widely used programming language, thanks to its easy learning curve, versatility, and support for modern paradigms. The language is used to create desktop apps, background services, web apps, and mobile apps. .NET Core is open source and compatible with Mac OS and Linux. There is no limit to what you can achieve with C# and .NET Core. This Learning Path begins with the basics of C# and object-oriented programming (OOP) and explores features of C#, such as tuples, pattern matching, and out variables. You will understand.NET Standard 2.0 class libraries and ASP.NET Core 2.0, and create professional websites, services, and applications. You will become familiar with mobile app development using Xamarin.Forms and learn to develop high-performing applications by writing optimized code with various profiling techniques. By the end of C# 7 and .NET: Designing Modern Cross-platform Applications, you will have all the knowledge required to build modern, cross-platform apps using C ...
Tableau 10 Complete Reference
Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also cov ...
Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10. This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You'll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also cov ...
Apache Spark 2: Data Processing and Real-Time Analytics
Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your own data flow and machine learning programs on this platform. You will work with the different modules in Apache Spark, such as interactive querying with Spark SQL, using DataFrames and datasets, implementing streaming analytics with Spark Streaming, and applying machine learning and deep learning techniques on Spark using MLlib and various external tools. By the end of this elaborately designed Learning Path, you will have all the knowledge you need to master Apache Spark, and build your own big data processing and analytics pipeline quickly and without any hassle. ...
Machine Learning in the Oil and Gas Industry
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and prod ...
Apply machine and deep learning to solve some of the challenges in the oil and gas industry. The book begins with a brief discussion of the oil and gas exploration and production life cycle in the context of data flow through the different stages of industry operations. This leads to a survey of some interesting problems, which are good candidates for applying machine and deep learning approaches. The initial chapters provide a primer on the Python programming language used for implementing the algorithms; this is followed by an overview of supervised and unsupervised machine learning concepts. The authors provide industry examples using open source data sets along with practical explanations of the algorithms, without diving too deep into the theoretical aspects of the algorithms employed. Machine Learning in the Oil and Gas Industry covers problems encompassing diverse industry topics, including geophysics (seismic interpretation), geological modeling, reservoir engineering, and prod ...
Practical Glimpse
Learn how to edit images and create compelling digital art with Glimpse, the newest open source alternative to Adobe Photoshop and GIMP. This book explores Glimpse's broad selection of tools and features that can create beautiful (raster) digital art; painting, drawings, and art created from photos by applying one of the many filters to create artistic effects. You will quickly become acquainted with this powerful program and understand how to use workspace tools and layers. You will learn step-by-step how to correct exposure, digitally retouch and repair damaged photos, and handle just about any photo editing task - even colorizing grayscale images. Practice files are provided with step-by-step instructions to jump into photo editing and art creation. Glimpse is a powerful program that is a viable alternative to Adobe Photoshop and other proprietary software. The possibilities of the art one can create are almost limitless - get started with it using this book today. ...
Learn how to edit images and create compelling digital art with Glimpse, the newest open source alternative to Adobe Photoshop and GIMP. This book explores Glimpse's broad selection of tools and features that can create beautiful (raster) digital art; painting, drawings, and art created from photos by applying one of the many filters to create artistic effects. You will quickly become acquainted with this powerful program and understand how to use workspace tools and layers. You will learn step-by-step how to correct exposure, digitally retouch and repair damaged photos, and handle just about any photo editing task - even colorizing grayscale images. Practice files are provided with step-by-step instructions to jump into photo editing and art creation. Glimpse is a powerful program that is a viable alternative to Adobe Photoshop and other proprietary software. The possibilities of the art one can create are almost limitless - get started with it using this book today. ...
The Economics of Data, Analytics, and Digital Transformation
In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end ...
In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end ...
Practical Python Data Wrangling and Data Quality
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources; Understand and use programming basics in Python to wrangle data at scale; Organize, document, and structu ...
The world around us is full of data that holds unique insights and valuable stories, and this book will help you uncover them. Whether you already work with data or want to learn more about its possibilities, the examples and techniques in this practical book will help you more easily clean, evaluate, and analyze data so that you can generate meaningful insights and compelling visualizations. Complementing foundational concepts with expert advice, author Susan E. McGregor provides the resources you need to extract, evaluate, and analyze a wide variety of data sources and formats, along with the tools to communicate your findings effectively. This book delivers a methodical, jargon-free way for data practitioners at any level, from true novices to seasoned professionals, to harness the power of data. Use Python 3.8+ to read, write, and transform data from a variety of sources; Understand and use programming basics in Python to wrangle data at scale; Organize, document, and structu ...
Developing Microservices Architecture on Microsoft Azure with Open Source Technologies
Increasingly, organizations are modernizing application development by integrating open source technologies into a holistic architecture for delivering high-quality workloads to the cloud. This is a complete, step-by-step guide to building flexible microservices architecture by leveraging Microsoft Azure cloud services, together with key open source technologies such as Java, Node.JS, .NET Core and Angular. Through a realistic case study project, expert Microsoft engineers Ovais Mehboob Ahmed Khan and Arvind Chandaka guide you through every step of technical implementation required to achieve value: establishing end-to-end infrastructure, developing cloud-native applications, automating deployments, monitoring operations, and more. Microsoft engineers Ovais Mehboob Ahmed Khan and Arvind Chandaka show how to: Define application features and business requirements, and map them onto microservices using modeling techniques; Design microservices solution architecture that enables high-qu ...
Increasingly, organizations are modernizing application development by integrating open source technologies into a holistic architecture for delivering high-quality workloads to the cloud. This is a complete, step-by-step guide to building flexible microservices architecture by leveraging Microsoft Azure cloud services, together with key open source technologies such as Java, Node.JS, .NET Core and Angular. Through a realistic case study project, expert Microsoft engineers Ovais Mehboob Ahmed Khan and Arvind Chandaka guide you through every step of technical implementation required to achieve value: establishing end-to-end infrastructure, developing cloud-native applications, automating deployments, monitoring operations, and more. Microsoft engineers Ovais Mehboob Ahmed Khan and Arvind Chandaka show how to: Define application features and business requirements, and map them onto microservices using modeling techniques; Design microservices solution architecture that enables high-qu ...