Supervised Machine Learning with Python. Develop rich Python coding practices while exploring supervised machine learning

Taylor Smith

Supervised machine learning is used in a wide range of sectors, such as finance, online advertising, and analytics, to train systems to make pricing predictions, campaign adjustments, customer recommendations, and much more by learning from the data that is used to train it and making decisions on its own. This makes it crucial to know how a machine 'learns' under the hood.This book will guide you through the implementation and nuances of many popular supervised machine learning algorithms, and help you understand how they work. You’ll embark on this journey with a quick overview of supervised learning and see how it differs from unsupervised learning. You’ll then explore parametric models, such as linear and logistic regression, non-parametric methods, such as decision trees, and a variety of clustering techniques that facilitate decision-making and predictions. As you advance, you'll work hands-on with recommender systems, which are widely used by online companies to increase user interaction and enrich shopping potential. Finally, you’ll wrap up with a brief foray into neural networks and transfer learning.By the end of this book, you’ll be equipped with hands-on techniques and will have gained the practical know-how you need to quickly and effectively apply algorithms to solve new problems.

Automating Security Detection Engineering. A hands-on guide to implementing Detection as Code

Dennis Chow, David Bruskin

Today's global enterprise security programs grapple with constantly evolving threats. Even though the industry has released abundant security tools, most of which are equipped with APIs for integrations, they lack a rapid detection development work stream. This book arms you with the skills you need to automate the development, testing, and monitoring of detection-based use cases.You’ll start with the technical architecture, exploring where automation is conducive throughout the detection use case lifecycle. With the help of hands-on labs, you’ll learn how to utilize threat-informed defense artifacts and then progress to creating advanced AI-powered CI/CD pipelines to bolster your Detection as Code practices. Along the way, you'll develop custom code for EDRs, WAFs, SIEMs, CSPMs, RASPs, and NIDS. The book will also guide you in developing KPIs for program monitoring and cover collaboration mechanisms to operate the team with DevSecOps principles. Finally, you'll be able to customize a Detection as Code program that fits your organization's needs.By the end of the book, you'll have gained the expertise to automate nearly the entire use case development lifecycle for any enterprise.

Elasticsearch 7.0 Cookbook. Over 100 recipes for fast, scalable, and reliable search for your enterprise - Fourth Edition

Alberto Paro

Elasticsearch is a Lucene-based distributed search server that allows users to index and search unstructured content with petabytes of data. With this book, you'll be guided through comprehensive recipes on what's new in Elasticsearch 7, and see how to create and run complex queries and analytics.Packed with recipes on performing index mapping, aggregation, and scripting using Elasticsearch, this fourth edition of Elasticsearch Cookbook will get you acquainted with numerous solutions and quick techniques for performing both every day and uncommon tasks such as deploying Elasticsearch nodes, integrating other tools to Elasticsearch, and creating different visualizations. You will install Kibana to monitor a cluster and also extend it using a variety of plugins. Finally, you will integrate your Java, Scala, Python, and big data applications such as Apache Spark and Pig with Elasticsearch, and create efficient data applications powered by enhanced functionalities and custom plugins.By the end of this book, you will have gained in-depth knowledge of implementing Elasticsearch architecture, and you'll be able to manage, search, and store data efficiently and effectively using Elasticsearch.

BizTalk Server 2010 Cookbook. Over 50 recipes for developers and administrators looking to deliver well-built BizTalk solutions and environments with this book and

Steef-Jan Wiggers

BizTalk enables the integration and managment of automated business processes within or across organizational boundaries. To build a solid BizTalk solution, deploy a robust environment, and keep it running smoothly you sometimes need to broaden your spectrum, explore all possibilities, and choose the best solution for your purpose. By following the recipes in this book you will gain required knowledge and succeed in your implementation.With BizTalk Server 2010 Cookbook, you can leverage and hone your skills. More than 50 recipes will guide you in implementing BizTalk solutions, setting up a robust and well performing BizTalk environment, and choosing the right solution for monitoring it. As a developer or administrator you greatly benefit from taking these recipes to work.In this book a developer and administrator will see how to deploy, build, and maintain a BizTalk environment. How to apply patterns for robust orchestrations, messaging and testing.Administrators will learn to set up an environment using Microsoft best practices and tools to deliver a robust, performing and durable BizTalk environment. Besides setting up their environments administrators can also decide through a number of recipes how to monitor and maintain the environment. A developer can contribute to a healthy environment by implementing instrumentation in artefacts, applying well suited pattern(s) and testing the solutions built.

Mastering Azure Virtual Desktop. A practical guide to designing, implementing, and managing Azure Virtual Desktop environments - Second Edition

Ryan Mangan, Neil McLoughlin, Marcel Meurer, Christiaan Brinkhoff

Acquire in-depth knowledge for designing, building, and supporting Azure Virtual Desktop environments with the updated second edition of Mastering Azure Virtual Desktop. With content aligned with exam objectives, this book will help you ace the Microsoft AZ-140 exam.This book starts with an introduction to Azure Virtual Desktop before delving into the intricacies of planning and architecting its infrastructure. As you progress, you’ll learn about the implementation process, with an emphasis on best practices and effective strategies. You’ll explore key areas such as managing and controlling access, advanced monitoring with the new Azure Monitoring Agent, and advanced application deployment. You’ll also gain hands-on experience with essential features like the MSIX app attach, enhancing user experience and operational efficiency. Beyond advancing your skills, this book is a crucial resource for those preparing for the Microsoft Certified: Azure Virtual Desktop Specialty certification.By the end of this book, you’ll have a thorough understanding of the Azure Virtual Desktop environment, from design to implementation.

Java Deep Learning Essentials. Unlocking the next generation of predictive power

Yusuke Sugomori

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a Java developer, this book gives you a great opportunity to expand your skillset.Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you’ve got to grips with the fundamental mathematical principles, you’ll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you’ll also be able to get to grips with Theano and Caffe, two of the most important tools in Deep Learning today.By the end of the book, you’ll be ready to tackle Deep Learning with Java. Wherever you’ve come from – whether you’re a data scientist or Java developer – you will become a part of the Deep Learning revolution!

Java: Data Science Made Easy. Data collection, processing, analysis, and more

Richard M. Reese, Jennifer L. Reese, Alexey Grigorev

Data science is concerned with extracting knowledge and insights from a wide variety of data sources to analyse patterns or predict future behaviour. It draws from a wide array of disciplines including statistics, computer science, mathematics, machine learning, and data mining. In this course, we cover the basic as well as advanced data science concepts and how they are implemented using the popular Java tools and libraries.The course starts with an introduction of data science, followed by the basic data science tasks of data collection, data cleaning, data analysis, and data visualization. This is followed by a discussion of statistical techniques and more advanced topics including machine learning, neural networks, and deep learning. You will examine the major categories of data analysis including text, visual, and audio data, followed by a discussion of resources that support parallel implementation. Throughout this course, the chapters will illustrate a challenging data science problem, and then go on to present a comprehensive, Java-based solution to tackle that problem. You will cover a wide range of topics – from classification and regression, to dimensionality reduction and clustering, deep learning and working with Big Data. Finally, you will see the different ways to deploy the model and evaluate it in production settings.By the end of this course, you will be up and running with various facets of data science using Java, in no time at all.This course contains premium content from two of our recently published popular titles:- Java for Data Science- Mastering Java for Data Science

Learn Wireshark. A definitive guide to expertly analyzing protocols and troubleshooting networks using Wireshark - Second Edition

Lisa Bock

Wireshark is a popular and powerful packet analysis tool that helps network administrators investigate latency issues and potential attacks. Over the years, there have been many enhancements to Wireshark’s functionality. This book will guide you through essential features so you can capture, display, and filter data with ease. In addition to this, you’ll gain valuable tips on lesser-known configuration options, which will allow you to complete your analysis in an environment customized to suit your needs.This updated second edition of Learn Wireshark starts by outlining the benefits of traffic analysis. You’ll discover the process of installing Wireshark and become more familiar with the interface. Next, you’ll focus on the Internet Suite and then explore deep packet analysis of common protocols such as DNS, DHCP, HTTP, and ARP. The book also guides you through working with the expert system to detect network latency issues, create I/O and stream graphs, subset traffic, and save and export captures. Finally, you’ll understand how to share captures using CloudShark, a browser-based solution for analyzing packet captures.By the end of this Wireshark book, you’ll have the skills and hands-on experience you need to conduct deep packet analysis of common protocols and network troubleshooting as well as identify security issues.