Python Feature Engineering CookbookFeature engineering is invaluable for developing and enriching your machine learning models. In this cookbook, you will work with the best tools to streamline your feature engineering pipelines and techniques and simplify and improve the quality of your code.
Using Python libraries such as pandas, scikit-learn, Featuretools, and Feature-engine, you'll learn how to work with both continuous and discrete datasets and be able to transform features from unstructured datasets. You will develop the skills necessary to select the best features as well as the most suitable extraction techniques. This book will cover Python recipes that will help you automate feature engineering to simplify complex processes. You'll also get to grips with different feature engineering strategies, such as the box-cox transform, power transform, and log transform across machine learning, reinforcement learning, and natural language processing (NLP) domains.
By the end of this book, you'll have discovered ti ...
Distributed Tracing in PracticeSince most applications today are distributed in some fashion, monitoring their health and performance requires a new approach. Enter distributed tracing, a method of profiling and monitoring distributed applications - particularly those that use microservice architectures. There's just one problem: distributed tracing can be hard. But it doesn't have to be.
With this guide, you'll learn what distributed tracing is and how to use it to understand the performance and operation of your software. Key players at LightStep and other organizations walk you through instrumenting your code for tracing, collecting the data that your instrumentation produces, and turning it into useful operational insights. If you want to implement distributed tracing, this book tells you what you need to know.
You'll learn: The pieces of a distributed tracing deployment: instrumentation, data collection, and analysis; Best practices for instrumentation: methods for generating trace data from your services ...
High Performance Python, 2nd EditionYour 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 ...
Graph AlgorithmsLearn how graph algorithms can help you leverage relationships within your data to develop intelligent solutions and enhance your machine learning models. With this practical guide,
developers and data scientists will discover how graph analytics deliver value, whether they're used for building dynamic network models or forecasting real-world behavior.
Mark Needham and Amy Hodler from Neo4j explain how graph algorithms describe complex structures and reveal difficult-to-find patterns - from finding vulnerabilities and bottlenecks to detecting communities and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark and Neo4j, two of the most common choices for graph analytics.
Learn how graph analytics reveal more predictive elements in today's data; Understand how popular graph algorithms work and how they're applied; Use sample code and tips from more than 20 graph algorithm examples; Learn which alg ...
SQL Server 2019 Administration Inside OutDive into SQL Server 2019 administration - and really put your SQL Server DBA expertise to work. This supremely organized reference packs hundreds of timesaving solutions, tips, and workarounds - all you need to plan, implement, manage, and secure SQL Server 2019 in any production environment: on-premises, cloud, or hybrid. Six experts thoroughly tour DBA capabilities available in SQL Server 2019 Database Engine, SQL Server Data Tools, SQL Server Management Studio, PowerShell, and Azure Portal. You'll find extensive new coverage of Azure SQL, big data clusters, PolyBase, data protection, automation, and more. Discover how experts tackle today's essential tasks - and challenge yourself to new levels of mastery.
Explore SQL Server 2019's toolset, including the improved SQL Server Management Studio, Azure Data Studio, and Configuration Manager; Design, implement, manage, and govern on-premises, hybrid, or Azure database infrastructures; Install and configure SQL Server on Windows and L ...
The Project Managers Guide to Microsoft Project 2019This guide is an all-in-one training resource and reference that covers all versions found in the Microsoft Project 2019 suite. It is not a "how-to" manual covering the features and functions of the software, but is designed to explain and demonstrate why those features and functions are important to you as a project manager, allowing you to maximize the value of Microsoft Project 2019.
Each aspect of project-manager-specific coverage was selectively compiled by author and Microsoft Project expert Cicala over more than two decades of consulting, project management training, and managing real-world projects using Microsoft Project. Readers will appreciate the robust index and intuitively organized and learning-oriented chapters, and sub-sections for quick reference and problem solving. "Try it" exercises at the close of every chapter help ensure understanding of the content. ...
Practical MATLAB Modeling with SimulinkEmploy the essential and hands-on tools and functions of MATLAB's ordinary differential equation (ODE) and partial differential equation (PDE) packages, which are explained and demonstrated via interactive examples and case studies. This book contains dozens of simulations and solved problems via m-files/scripts and Simulink models which help you to learn programming and modeling of more difficult, complex problems that involve the use of ODEs and PDEs.
You'll become efficient with many of the built-in tools and functions of MATLAB/Simulink while solving more complex engineering and scientific computing problems that require and use differential equations. Practical MATLAB Modeling with Simulink explains various practical issues of programming and modelling.
After reading and using this book, you'll be proficient at using MATLAB and applying the source code from the book's examples as templates for your own projects in data science or engineering. ...
Spring Boot Persistence Best PracticesThis book is a collection of developer code recipes and best practices for persisting data using Spring, particularly Spring Boot. The book is structured around practical recipes, where each recipe discusses a performance case or performance-related case, and almost every recipe has one or more applications. Mainly, when we try to accomplish something (e.g., read some data from the database), there are several approaches to do it, and, in order to choose the best way, you have to know the implied trades-off from a performance perspective. You'll see that in the end, all these penalties slow down the application. Besides presenting the arguments that favor a certain choice, the application is written in Spring Boot style which is quite different than plain Hibernate.
Persistence is an important set of techniques and technologies for accessing and using data, and this book demonstrates that data is mobile regardless of specific applications and contexts. In Java development, persisten ...
Jakarta EE RecipesTake a problem-solution approach to programming enterprise Java applications and microservices for cloud-based solutions, enterprise database applications, and even small business web applications. This book provides effective and proven code snippets that you can immediately use to accomplish just about any task that you may encounter. You can feel confident using the reliable solutions that are demonstrated in this book in your personal or corporate environment.
Java EE was made open source under the Eclipse Foundation, and Jakarta EE is the new name for what used to be termed the Java Enterprise Edition Platform. This book helps you rejuvenate your Java expertise and put the platform's latest capabilities to use in quickly developing robust applications. If you are new to Jakarta EE, this book will help you learn features of the platform, and benefit from one of the most widely used and powerful technologies available for application development today.
Examples in Jakarta EE R ...
Unlocking Blockchain on AzureDesign, architect, and build Blockchain applications with Azure in industrial scenarios to revolutionize conventional processes and data security. This book will empower you to build better decentralized applications that have stronger encryption, better architectures, and effective deployment structures over the cloud.
You'll start with an overview of Blockchain, distributed networks, Azure components in Blockchain, such as Azure Workbench, and independent Blockchain-as-a-service solutions. Next, you'll move on to aspects of Blockchain transactions where the author discusses encryption and distribution along with practical examples. You'll cover permissioned Blockchains and distributed ledgers with the help of use cases of financial institutions, followed by code and development aspects of smart contracts. Here, you will learn how to utilise the templates provided by Azure Resource Manager to quickly develop an Ethereum-based smart contract.
Further, you will go through Blockcha ...