Practical Oracle Cloud Infrastructure
Use this fast-paced and comprehensive guide to build cloud-based solutions on Oracle Cloud Infrastructure. You will understand cloud infrastructure, and learn how to launch new applications and move existing applications to Oracle Cloud. Emerging trends in software architecture are covered such as autonomous platforms, infrastructure as code, containerized applications, cloud-based container orchestration with managed Kubernetes, and running serverless workloads using open-source tools. Practical examples are provided. This book teaches you how to self-provision the cloud resources you require to run and scale your custom cloud-based applications using a convenient web console and programmable APIs, and you will learn how to manage your infrastructure as code with Terraform. You will be able to plan, design, implement, deploy, run, and monitor your production-grade and fault-tolerant cloud software solutions in Oracle's data centers across the world, paying only for the resources you ...
Use this fast-paced and comprehensive guide to build cloud-based solutions on Oracle Cloud Infrastructure. You will understand cloud infrastructure, and learn how to launch new applications and move existing applications to Oracle Cloud. Emerging trends in software architecture are covered such as autonomous platforms, infrastructure as code, containerized applications, cloud-based container orchestration with managed Kubernetes, and running serverless workloads using open-source tools. Practical examples are provided. This book teaches you how to self-provision the cloud resources you require to run and scale your custom cloud-based applications using a convenient web console and programmable APIs, and you will learn how to manage your infrastructure as code with Terraform. You will be able to plan, design, implement, deploy, run, and monitor your production-grade and fault-tolerant cloud software solutions in Oracle's data centers across the world, paying only for the resources you ...
Refactoring Legacy T-SQL for Improved Performance
Breathe new life into older applications by refactoring T-SQL queries and code using modern techniques. This book shows you how to significantly improve the performance of older applications by finding common anti-patterns in T-SQL code, then rewriting those anti-patterns using new functionality that is supported in current versions of SQL Server, including SQL Server 2019. The focus moves through the different types of database objects and the code used to create them, discussing the limitations and anti-patterns commonly found for each object type in your database. Legacy code isn't just found in queries and external applications. It's also found in the definitions of underlying database objects such as views and tables. This book helps you quickly find problematic code throughout the database and points out where and how modern solutions can replace older code, thereby making your legacy applications run faster and extending their lifetimes. Author Lisa Bohm explains the logic be ...
Breathe new life into older applications by refactoring T-SQL queries and code using modern techniques. This book shows you how to significantly improve the performance of older applications by finding common anti-patterns in T-SQL code, then rewriting those anti-patterns using new functionality that is supported in current versions of SQL Server, including SQL Server 2019. The focus moves through the different types of database objects and the code used to create them, discussing the limitations and anti-patterns commonly found for each object type in your database. Legacy code isn't just found in queries and external applications. It's also found in the definitions of underlying database objects such as views and tables. This book helps you quickly find problematic code throughout the database and points out where and how modern solutions can replace older code, thereby making your legacy applications run faster and extending their lifetimes. Author Lisa Bohm explains the logic be ...
Introducing Algorithms in C
Study elementary and complex algorithms with clear examples and implementations in C. This book introduces data types (simple and structured) and algorithms with graphical and textual explanations. In the next sections, you'll cover simple and complex standard algorithms with their flowcharts: everything is integrated with explanations and tables to give a step-by-step evolution of the algorithms. The main algorithms are: the sum of three or n numbers in a loop, decimal-to-binary conversion, maximum and minimum search, linear/sequential search, binary search, bubble sort, selection sort, merging of two sorted arrays, reading characters from a file, stack management, and factorial and Fibonacci sequences. The last section of Introducing Algorithms in C is devoted to the introduction of the C language and the implementation of the code, which is connected to the studied algorithms. The book is full of screenshots and illustrations showing the meaning of the code. - Implement a ...
Study elementary and complex algorithms with clear examples and implementations in C. This book introduces data types (simple and structured) and algorithms with graphical and textual explanations. In the next sections, you'll cover simple and complex standard algorithms with their flowcharts: everything is integrated with explanations and tables to give a step-by-step evolution of the algorithms. The main algorithms are: the sum of three or n numbers in a loop, decimal-to-binary conversion, maximum and minimum search, linear/sequential search, binary search, bubble sort, selection sort, merging of two sorted arrays, reading characters from a file, stack management, and factorial and Fibonacci sequences. The last section of Introducing Algorithms in C is devoted to the introduction of the C language and the implementation of the code, which is connected to the studied algorithms. The book is full of screenshots and illustrations showing the meaning of the code. - Implement a ...
Pro T-SQL 2019
Design and write simple and efficient T-SQL code in SQL Server 2019 and beyond. Writing T-SQL that pulls back correct results can be challenging. This book provides the help you need in writing T-SQL that performs fast and is easy to maintain. You also will learn how to implement version control, testing, and deployment strategies. Hands-on examples show modern T-SQL practices and provide straightforward explanations. Attention is given to selecting the right data types and objects when designing T-SQL solutions. Author Elizabeth Noble teaches you how to improve your T-SQL performance through good design practices that benefit programmers and ultimately the users of the applications. You will know the common pitfalls of writing T-SQL and how to avoid those pitfalls going forward. - Choose correct data types and database objects when designing T-SQL - Write T-SQL that searches data efficiently and uses hardware effectively - Implement source control and testing methods to stream ...
Design and write simple and efficient T-SQL code in SQL Server 2019 and beyond. Writing T-SQL that pulls back correct results can be challenging. This book provides the help you need in writing T-SQL that performs fast and is easy to maintain. You also will learn how to implement version control, testing, and deployment strategies. Hands-on examples show modern T-SQL practices and provide straightforward explanations. Attention is given to selecting the right data types and objects when designing T-SQL solutions. Author Elizabeth Noble teaches you how to improve your T-SQL performance through good design practices that benefit programmers and ultimately the users of the applications. You will know the common pitfalls of writing T-SQL and how to avoid those pitfalls going forward. - Choose correct data types and database objects when designing T-SQL - Write T-SQL that searches data efficiently and uses hardware effectively - Implement source control and testing methods to stream ...
Advanced Deep Learning with Python
In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured da ...
In order to build robust deep learning systems, you'll need to understand everything from how neural networks work to training CNN models. In this book, you'll discover newly developed deep learning models, methodologies used in the domain, and their implementation based on areas of application. You'll start by understanding the building blocks and the math behind neural networks, and then move on to CNNs and their advanced applications in computer vision. You'll also learn to apply the most popular CNN architectures in object detection and image segmentation. Further on, you'll focus on variational autoencoders and GANs. You'll then use neural networks to extract sophisticated vector representations of words, before going on to cover various types of recurrent networks, such as LSTM and GRU. You'll even explore the attention mechanism to process sequential data without the help of recurrent neural networks (RNNs). Later, you'll use graph neural networks for processing structured da ...
C# 8.0 in a Nutshell
When you have questions about C# 8.0 or .NET Core, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, but with its continual growth there's so much more to learn. In the tradition of the O'Reilly Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, C# 8.0 in a Nutshell provides intermediate and advanced programmers with a concise map of C# and .NET knowledge that also plumbs significant depths. Get up to speed on C#, from syntax and variables to advanced topics such as pointers, closures, and patterns; Dig deep into LINQ with three chapters dedicated to the topic; Explore concurrency and asynchrony, advanced threading, and parallel programming; Work with .NET features, including regular expressions, networking, serialization, spans, reflection, and cryptography; Delve into Roslyn, the modular C# compiler as a service ...
When you have questions about C# 8.0 or .NET Core, this best-selling guide has the answers you need. C# is a language of unusual flexibility and breadth, but with its continual growth there's so much more to learn. In the tradition of the O'Reilly Nutshell guides, this thoroughly updated edition is simply the best one-volume reference to the C# language available today. Organized around concepts and use cases, C# 8.0 in a Nutshell provides intermediate and advanced programmers with a concise map of C# and .NET knowledge that also plumbs significant depths. Get up to speed on C#, from syntax and variables to advanced topics such as pointers, closures, and patterns; Dig deep into LINQ with three chapters dedicated to the topic; Explore concurrency and asynchrony, advanced threading, and parallel programming; Work with .NET features, including regular expressions, networking, serialization, spans, reflection, and cryptography; Delve into Roslyn, the modular C# compiler as a service ...
Building Secure and Reliable Systems
Can a system be considered truly reliable if it isn't fundamentally secure? Or can it be considered secure if it's unreliable? Security is crucial to the design and operation of scalable systems in production, as it plays an important part in product quality, performance, and availability. In this book, experts from Google share best practices to help your organization design scalable and reliable systems that are fundamentally secure. Two previous O'Reilly books from Google - Site Reliability Engineering and The Site Reliability Workbook - demonstrated how and why a commitment to the entire service lifecycle enables organizations to successfully build, deploy, monitor, and maintain software systems. In this latest guide, the authors offer insights into system design, implementation, and maintenance from practitioners who specialize in security and reliability. They also discuss how building and adopting their recommended best practices requires a culture that's supportive of such c ...
Can a system be considered truly reliable if it isn't fundamentally secure? Or can it be considered secure if it's unreliable? Security is crucial to the design and operation of scalable systems in production, as it plays an important part in product quality, performance, and availability. In this book, experts from Google share best practices to help your organization design scalable and reliable systems that are fundamentally secure. Two previous O'Reilly books from Google - Site Reliability Engineering and The Site Reliability Workbook - demonstrated how and why a commitment to the entire service lifecycle enables organizations to successfully build, deploy, monitor, and maintain software systems. In this latest guide, the authors offer insights into system design, implementation, and maintenance from practitioners who specialize in security and reliability. They also discuss how building and adopting their recommended best practices requires a culture that's supportive of such c ...
Cassandra: The Definitive Guide, 3rd Edition
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition - updated for Cassandra 4.0 - provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. If you're a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra's speed and flexibility. Understand Cassandra's distributed and decentralized structure; Use the Cassandra Query Language (CQL) and cqlsh - the CQL shell; Create a working data model and compare it with an equivalent relational model; Develop sample applications using ...
Imagine what you could do if scalability wasn't a problem. With this hands-on guide, you'll learn how the Cassandra database management system handles hundreds of terabytes of data while remaining highly available across multiple data centers. This third edition - updated for Cassandra 4.0 - provides the technical details and practical examples you need to put this database to work in a production environment. Authors Jeff Carpenter and Eben Hewitt demonstrate the advantages of Cassandra's nonrelational design, with special attention to data modeling. If you're a developer, DBA, or application architect looking to solve a database scaling issue or future-proof your application, this guide helps you harness Cassandra's speed and flexibility. Understand Cassandra's distributed and decentralized structure; Use the Cassandra Query Language (CQL) and cqlsh - the CQL shell; Create a working data model and compare it with an equivalent relational model; Develop sample applications using ...
Practical Statistics for Data Scientists, 2nd Edition
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you'll learn: Why exploratory data analysis is a key preliminary step in data science; How random sampling can reduce bias and yield a higher-quality dataset, even with big data; How the principles of experimental design yield definitive answers to ...
Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not. Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format. With this book, you'll learn: Why exploratory data analysis is a key preliminary step in data science; How random sampling can reduce bias and yield a higher-quality dataset, even with big data; How the principles of experimental design yield definitive answers to ...
High Performance Python, 2nd Edition
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers; Learn how Python abstracts the underlying computer architecture; Use profiling to find bottlenecks in CPU time and memory usage; Write efficient programs by choosing appropriate data structures; Speed up matrix ...
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python's implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers; Learn how Python abstracts the underlying computer architecture; Use profiling to find bottlenecks in CPU time and memory usage; Write efficient programs by choosing appropriate data structures; Speed up matrix ...