Bücher veröffentlicht von Packt Publishing Limited

Microsoft System Center Orchestrator 2016 simplifies the process of automating system administration tasks and provides a complete solution that goes beyond basic automation. In this practical cookbook you will learn how to explore System Center 2016 by creating runbooks to control and automate every feature possible.

Perl is a family of high-level, general-purpose, interpreted, dynamic programming languages consisting of Perl 5 and Perl 6. Perl 6 helps developers write concise and declarative code that is easy to maintain. This book is an end-to-end guide that will help non-Perl developers get to grips with the language and use it to solve real-world problems.

This book examines machine learning models including k-nearest neighbors, logistic regression, naive Bayes, random forests, and support vector machines. You will work through document classification, image recognition, and other example problems.

This book will teach you all it takes to perform complex statistical computations required for Machine Learning. You will gain information on statistics behind supervised learning, unsupervised learning, reinforcement learning, and more. Understand the real-world examples that discuss the statistical side of Machine Learning and familiarize your...

Regular expressions are a powerful tool in the programmer's toolbox and allow pattern matching. They are also used for manipulating text and data. This book will provide you with the know-how (and practical examples) to solve real-world problems using regex in Java.

Suitable for information security professionals, forensics practitioners, and students, this title guides them through the entire spectrum of tasks associated with incident response, starting with preparatory activities associated with creating an incident response plan and creating a digital forensics capability within your own organization.

Offers practical techniques to build cloud-native apps that dynamically scale to handle virtually any volume of data, traffic, or users. This book showcases the tools and techniques you need build robust and resilient cloud native applications in Python. It shows you how to build, test, and scale their Python-based applications.

Helps you build a strong foundation for entering the world of machine learning and data science. This book shows you how to acquaint yourself with important elements of Machine Learning; understand the feature selection and feature engineering process; and assess performance and error trade-offs of Linear Regression, among others.

Utilize Python microservices to break down your app development into bitesize pieces and deploy them as cloud services.

Over the last few years, Scala has been adopted increasingly, especially in the field of data science and analytics, along with Apache Spark, which is built on Scala and is widely used in the field of analytics. With this book, you'll learn how to leverage the power of both Scala and Spark to make sense of big data.

Build, Manage and Improve your infrastructure effortlessly. About This Book - An up-to-date and comprehensive resource on Terraform that lets you quickly and efficiently launch your infrastructure - Learn how to implement your infrastructure as code and make secure, effective changes to your infrastructure - Learn to build multi-cloud fault-tolerant systems and simplify the management and orchestration of even the largest scale and most complex cloud infrastructures Who This Book Is For This book is for developers and operators who already have some exposure to working with infrastructure but want to improve their workflow and introduce infrastructure as a code practice. Knowledge of essential Amazon Web Services components (EC2, VPC, IAM) would help contextualize the examples provided. Basic understanding of Jenkins and Shell scripts will be helpful for the chapters on the production usage of Terraform. What You Will Learn - Understand what Infrastructure as Code (IaC) means and why it matters - Install, configure, and deploy Terraform - Take full control of your infrastructure in the form of code - Manage complete infrastructure, starting with a single server and scaling beyond any limits - Discover a great set of production-ready practices to manage infrastructure - Set up CI/CD pipelines to test and deliver Terraform stacks - Construct templates to simplify more complex provisioning tasks In Detail Terraform is a tool used to efficiently build, configure, and improve the production infrastructure. It can manage the existing infrastructure as well as create custom in-house solutions. This book shows you when and how to implement infrastructure as a code practices with Terraform. It covers everything necessary to set up the complete management of infrastructure with Terraform, starting with the basics of using providers and resources. It is a comprehensive guide that begins with very small infrastructure templates and takes you all the way to managing complex systems, all using concrete examples that evolve over the course of the book. The book ends with the complete workflow of managing a production infrastructure as code-this is achieved with the help of version control and continuous integration. The readers will also learn how to combine multiple providers in a single template and manage different code bases with many complex modules. It focuses on how to set up continuous integration for the infrastructure code. The readers will be able to use Terraform to build, change, and combine infrastructure safely and efficiently. Style and approach This book will help and guide you to implement Terraform in your infrastructure. The readers will start by working on very small infrastructure templates and then slowly move on to manage complex systems, all by using concrete examples that will evolve during the course of the book.

Explores various possibilities with deep learning and enables you to gain insights from data using Google's brainchild - TensorFlow. This guide shows you how to set up your computing environment and install TensorFlow; build simple TensorFlow graphs for everyday computations; and apply logistic regression for classification with TensorFlow.

The job of a data scientist is one of the most lucrative jobs out there today - it involves analyzing large amounts of data, and gathering actionable business insights from it using a variety of tools. This book empowers you to conduct data analysis and perform efficient machine learning using Python.

Natural Language Processing is a field of computational linguistics and artificial intelligence that deals with human-computer interaction. The numbers of human-computer interaction instances are increasing so it's becoming imperative that computers comprehend all major natural languages. Python's powerful tools and libraries are evolved so much.

AWS provides a huge range of managed services. While each is well documented, figuring out how to use them together to build a business infrastructure is less clear. In this book, you'll see how the most successful tech start-ups launch and scale their services on AWS and how you can too.

This book covers a complete overview of Deep Learning with Theano, a Python-based library that makes optimizing numerical expressions easy.Practical code examples address supervised, unsupervised, generative and reinforcement learning for image recognition, natural language processing, or game strategy, with best performing nets and principles.

Apache Mesos is the first Open Source cluster manager that handles the workload in distributed environment through dynamic resource sharing and isolation. It is good for deployment and management of applications in large-scale cluster environments.