Datadog Cloud Monitoring Quick Start Guide. Proactively create dashboards, write scripts, manage alerts, and monitor containers using Datadog

Thomas Kurian Theakanath

Datadog is an essential cloud monitoring and operational analytics tool which enables the monitoring of servers, virtual machines, containers, databases, third-party tools, and application services. IT and DevOps teams can easily leverage Datadog to monitor infrastructure and cloud services, and this book will show you how.The book starts by describing basic monitoring concepts and types of monitoring that are rolled out in a large-scale IT production engineering environment. Moving on, the book covers how standard monitoring features are implemented on the Datadog platform and how they can be rolled out in a real-world production environment. As you advance, you'll discover how Datadog is integrated with popular software components that are used to build cloud platforms. The book also provides details on how to use monitoring standards such as Java Management Extensions (JMX) and StatsD to extend the Datadog platform. Finally, you'll get to grips with monitoring fundamentals, learn how monitoring can be rolled out using Datadog proactively, and find out how to extend and customize the Datadog platform.By the end of this Datadog book, you will have gained the skills needed to monitor your cloud infrastructure and the software applications running on it using Datadog.

SDL Game Development. If you're good with C++ and object oriented programming, this book utilizes your skills to create 2D games using the Simple DirectMedia Layer API. Practical tutorials include the development of two wickedly good games

Shaun Mitchell

SDL 2.0 is the latest release of the popular Simple DirectMedia Layer API, which is designed to make life easier for C++ developers, allowing you simple low-level access to various multiplatform audio, graphics, and input devices.SDL Game Development guides you through creating your first 2D game using SDL and C++. It takes a clear and practical approach to SDL game development, ensuring that the focus remains on creating awesome games.Starting with the installation and setup of SDL, you will quickly become familiar with useful SDL features, covering sprites, state management, and OOP, leading to a reusable framework that is extendable for your own games. SDL Game Development culminates in the development of two exciting action games that utilize the created framework along with tips to improve the framework.

Building Wireless Sensor Networks Using Arduino. Leverage the powerful Arduino and XBee platforms to monitor and control your surroundings

Matthijs Kooijman

Terraform for Google Cloud Essential Guide. Learn how to provision infrastructure in Google Cloud securely and efficiently

Bernd Nordhausen

Google Cloud has adopted Terraform as the standard Infrastructure as Code tool. This necessitates a solid understanding of Terraform for any cloud architect or engineer working on Google Cloud. Yet no specific resources are available that focus on how to use Terraform on Google Cloud.This is the first book that teaches Terraform specifically for Google Cloud. You will take a journey from the basic concepts through to deploying complex architectures using Terraform. Using extensive code examples, you will receive guidance on how to authenticate Terraform in Google Cloud. As you advance, you’ll get to grips with all the essential concepts of the Terraform language as applied to Google Cloud and deploy complete working architectures at the push of a button. Finally, you’ll also be able to improve your Terraform workflow using Google Cloud native and third-party tools.By the end of this Terraform book, you will have gained a thorough understanding of Terraform and how to use it on Google Cloud, and be able to develop effective Terraform code, build reusable code, and utilize public domain Terraform modules to deploy on Google Cloud faster and more securely.

The Complete Power BI Interview Guide. A modern approach to acing the data analyst interview and landing your dream job

Sandielly Ortega Polanco, Gogula Aryalingam, Abu Bakar Nisar Alvi

The Complete Power Interview Guide helps you excel in a Power BI interview, secure desired roles, and be ready with the knowledge and skills to ace your role from the first day. Whether you're beginning your career journey or transitioning into a data analytics role, this guide offers hands-on skills and interview questions you need to succeed as a BI or data analyst. This book also offers supplemental content for PowerBI certification exams like PL-300. The book will equip you with the knowledge and strategies to effectively navigate the competitive job market. From creating an outstanding online professional profile to optimizing your resume and building a compelling work portfolio, you'll learn how to establish a strong personal brand. The essentials of Power BI, including data preparation, data modeling, DAX programming, expert report development, and impactful storytelling, are covered in-depth through real-world examples and valuable tips.By the end of this book, you'll have the confidence to interview for Power BI roles, navigate technical assessments, answer behavioral questions, and tackle case studies. You’ll have gained applied knowledge and the competitive edge needed to succeed in the data analytics job market and stay ahead of industry trends for career advancement.

Machine Learning with Go Quick Start Guide. Hands-on techniques for building supervised and unsupervised machine learning workflows

Michael Bironneau, Toby Coleman

Machine learning is an essential part of today's data-driven world and is extensively used across industries, including financial forecasting, robotics, and web technology. This book will teach you how to efficiently develop machine learning applications in Go.The book starts with an introduction to machine learning and its development process, explaining the types of problems that it aims to solve and the solutions it offers. It then covers setting up a frictionless Go development environment, including running Go interactively with Jupyter notebooks. Finally, common data processing techniques are introduced.The book then teaches the reader about supervised and unsupervised learning techniques through worked examples that include the implementation of evaluation metrics. These worked examples make use of the prominent open-source libraries GoML and Gonum.The book also teaches readers how to load a pre-trained model and use it to make predictions. It then moves on to the operational side of running machine learning applications: deployment, Continuous Integration, and helpful advice for effective logging and monitoring.At the end of the book, readers will learn how to set up a machine learning project for success, formulating realistic success criteria and accurately translating business requirements into technical ones.

Java Deep Learning Cookbook. Train neural networks for classification, NLP, and reinforcement learning using Deeplearning4j

Rahul Raj

Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently.This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results.By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java.

Hands-On Data Preprocessing in Python. Learn how to effectively prepare data for successful data analytics

Roy Jafari

Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects. With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data. You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment. The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data.By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.