AWS DevOps Simplified. Build a solid foundation in AWS to deliver enterprise-grade software solutions at scale

Akshay Kapoor, Paul Duvall

DevOps and AWS are the two key enablers for the success of any modern software-run business. DevOps accelerates software delivery, while AWS offers a plethora of services, allowing developers to prioritize business outcomes without worrying about undifferentiated heavy lifting. This book focuses on the synergy between them, equipping you with strong foundations, hands-on examples, and a strategy to accelerate your DevOps journey on AWS.AWS DevOps Simplified is a practical guide that starts with an introduction to AWS DevOps offerings and aids you in choosing a cloud service that fits your company's operating model. Following this, it provides hands-on tutorials on the GitOps approach to software delivery, covering immutable infrastructure and pipelines, using tools such as Packer, CDK, and CodeBuild/CodeDeploy. Additionally, it provides you with a deep understanding of AWS container services and how to implement observability and DevSecOps best practices to build and operate your multi-account, multi-Region AWS environments.By the end of this book, you’ll be equipped with solutions and ready-to-deploy code samples that address common DevOps challenges faced by enterprises hosting workloads in the cloud.

Julia High Performance. Design and develop high performing programs with Julia

Avik Sengupta

Julia is a high performance, high-level dynamic language designed to address the requirements of high-level numerical and scientific computing. Julia brings solutions to the complexities faced by developers while developing elegant and high performing code. Julia High Performance will take you on a journey to understand the performance characteristics of your Julia programs, and enables you to utilize the promise of near C levels of performance in Julia.You will learn to analyze and measure the performance of Julia code, understand how to avoid bottlenecks, and design your program for the highest possible performance. In this book, you will also see how Julia uses type information to achieve its performance goals, and how to use multuple dispatch to help the compiler to emit high performance machine code. Numbers and their arrays are obviously the key structures in scientific computing – you will see how Julia’s design makes them fast. The last chapter will give you a taste of Julia’s distributed computing capabilities.

Elasticsearch 8.x Cookbook. Over 180 recipes to perform fast, scalable, and reliable searches for your enterprise - Fifth Edition

Alberto Paro

Elasticsearch is a Lucene-based distributed search engine at the heart of the Elastic Stack that allows you to index and search unstructured content with petabytes of data. With this updated fifth edition, you'll cover comprehensive recipes relating to what's new in Elasticsearch 8.x and see how to create and run complex queries and analytics.The recipes will guide you through performing index mapping, aggregation, working with queries, and scripting using Elasticsearch. You'll focus on numerous solutions and quick techniques for performing both common and uncommon tasks such as deploying Elasticsearch nodes, using the ingest module, working with X-Pack, and creating different visualizations. As you advance, you'll learn how to manage various clusters, restore data, and install Kibana to monitor a cluster and extend it using a variety of plugins. Furthermore, you'll understand how to 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 Elasticsearch cookbook, you'll have gained in-depth knowledge of implementing the Elasticsearch architecture and be able to manage, search, and store data efficiently and effectively using Elasticsearch.

jQuery UI Cookbook. For jQuery UI developers this is the ultimate guide to maximizing the potential of your user interfaces. Full of great practical recipes that cover every widget in the framework, it's an essential manual

Adam Boduch

jQuery UI is the quintessential framework for creating professional user interfaces. While jQuery core lays the foundation for interaction with the DOM and handling events, jQuery UI fills in the user interaction gap. This book will give you a huge productivity boost out of the box with jQuery UI, and help you understand the framework, inside and out.jQuery UI Cookbook provides you with practical recipes featuring in-depth coverage of every widget in the framework, including how to address limitations that impact your everyday development activities with these widgets. You'll get a better idea of the big picture – how the framework is composed, how the widgets relate to one another, and how to build on those patterns.Be it a minor tweak on the visual design of a progress bar or a fundamental change in a widget to meet your needs, jQuery UI Cookbook covers scenarios both big and small. You can show reminders as tooltips, apply a variety of effects to the menu widget, and start interactions between the dialog widget and API data using deferred objects. These and many more interesting tasks are covered in this book, which can be done with smooth learning and great understanding. You will see how button widgets can fill the width of their containing element, making the layout more consistent. Tabs can be sorted and moved between widgets. You will learn how to do all these things within the context of the big picture, by finding out why the components work the way they do, making you well-versed in jQuery UI.

Learning Tableau 2020. Create effective data visualizations, build interactive visual analytics, and transform your organization - Fourth Edition

Joshua N. Milligan

Learning Tableau strengthens your command on Tableau fundamentals and builds on advanced topics.The book starts by taking you through foundational principles of Tableau. We then demonstrate various types of connections and how to work with metadata. We teach you to use a wide variety of visualizations to analyze and communicate the data, and introduce you to calculations and parameters. We then take an in-depth look at level of detail (LOD) expressions and use them to solve complex data challenges. Up next, we show table calculations, how to extend and alter default visualizations, build an interactive dashboard, and master the art of telling stories with data.This Tableau book will introduce you to visual statistical analytics capabilities, create different types of visualizations and dynamic dashboards for rich user experiences. We then move on to maps and geospatial visualization, and the new Data Model capabilities introduced in Tableau 2020.2. You will further use Tableau Prep’s ability to clean and structure data and share the stories contained in your data.By the end of this book, you will be proficient in implementing the powerful features of Tableau 2020 for decision-making.

OpenCV with Python Blueprints. Design and develop advanced computer vision projects using OpenCV with Python

Michael Beyeler

Microsoft Exchange 2013 Cookbook. Get the most out of Microsoft Exchange with this comprehensive guide. Structured around a series of clear, step-by-step exercises it will help you deploy and configure both basic and advanced features for your enterprise

Michael Van Horenbeeck, Peter De Tender

OpenAI GPT For Python Developers. The art and science of building AI-powered apps with GPT-4, Whisper, Weaviate, and beyond

Aymen El Amri

“OpenAI GPT for Python Developers” is meticulously crafted to provide Python developers with a deep dive into the mechanics and applications of GPT technology, beginning with a captivating narrative on the evolution of OpenAI and the fundamental workings of GPT models. As readers progress, they will be expertly guided through the essential steps of setting up a development environment tailored for AI innovations, coupled with insightful advice on selecting the most appropriate GPT model to suit specific project needs.The guide progresses into practical tutorials that cover the implementation of chat completions and the art of prompt engineering, providing a solid foundation in harnessing the capabilities of GPT for generating human-like text responses. Practical applications are further expanded with discussions on the creation of autonomous AI-to-AI dialogues, the development of AI avatars, and the strategic use of AI in interactive applications.In addition to technical skills, this book addresses the ethical implications and prospects of AI technologies, encouraging a holistic view of AI development. The guide is enriched with detailed examples, step-by-step tutorials, and comprehensive explanations that illuminate the theoretical aspects and emphasize practical implementation.

Learning C# by Developing Games with Unity 3D Beginner's Guide. The beauty of this book is that it assumes absolutely no knowledge of coding at all. Starting from very first principles it will end up giving you an excellent grounding in the writing of C# code and scripts

Terry Norton

For the absolute beginner to any concept of programming, writing a script can appear to be an impossible hurdle to overcome. The truth is, there are only three simple concepts to understand: 1) having some type of information; 2) using the information; and 3) communicating the information. Each of these concepts is very simple and extremely important. These three concepts are combined to access the feature set provided by Unity.Learning C# by Developing Games with Unity 3D Beginner's Guide assumes that you know nothing about programming concepts. First you will learn the absolute basics of programming using everyday examples that you already know. As you progress through the book, you will find that C# is not a foreign language after all, because you already know the words. With a few keywords and using substitution, before you know it, you'll be thinking in code.The book starts by explaining in simple terms the three concepts you need for writing C# code and scripts: 1) variables to hold information; 2) methods (functions) to use the information; and 3) Dot Syntax to communicate the information where it's needed. The book builds on these concepts to open up the world of C# coding and Unity scripting. You will use this new power to access the features provided in Unity's Scripting Reference.The first half of this book is devoted to the code writing beginner. The concepts of variables, methods, Dot Syntax, and decision processing are fully explained. Since C# is an actual programming language, we take advantage of this to develop a State Machine to help control and organize each phase of a Unity project. Once the basic programming concepts are established and we have some State Machine organization, the features and power of Unity are accessed using the Scripting Reference.If you're looking to learn C# for Unity then this is the book that offers everything you need and more - so discover what C# offers today and see your work come to life as complete games!

Realistic Asset Creation with Adobe Substance 3D. Create materials, textures, filters, and 3D models using Substance 3D Painter, Designer, and Stager

Zeeshan Jawed Shah

Adobe Substance 3D is a comprehensive suite complete with everything an artist needs to create stunning 3D digital materials. Getting a grip on the ecosystem of apps can be challenging for beginners, which is where Realistic Asset Creation with Adobe Substance 3D comes in!This practical guide doesn't bombard you with reams of textual information. Instead, you get an interactive, project-based book that’ll help you gain sound knowledge of Adobe Substance 3D and set you on the right path toward a career in 3D design. You’ll start off with the rudiments of Adobe Substance 3D Painter, which will enable you to acquire the skills needed to work with layers, masks, shelves, textures, and more. Next, you’ll move on to Adobe Substance 3D Designer and become well-acquainted with this node-based design tool as you progress through the chapters. The final section is devoted to Adobe Substance 3D Stager, which teaches you to build complex 3D scenes and visualize your edits in real time.By the end of this Adobe book, you’ll have gained a solid understanding of Adobe Substance 3D and developed the skills to build a comprehensive portfolio of work, setting you up for a lucrative career in 3D design.

Learning Robotics Using Python. Bring robotics projects to life with Python! Discover how to harness everything from Blender to ROS and OpenCV with one of our most popular robotics books

Marek Suppa, Lentin Joseph

Learning Predictive Analytics with Python. Click here to enter text

Ashish Kumar

Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form - It needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Learning to predict who would win, lose, buy, lie, or die with Python is an indispensable skill set to have in this data age. This book is your guide to getting started with Predictive Analytics using Python. You will see how to process data and make predictive models from it. We balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and numpy. You’ll start by getting an understanding of the basics of predictive modeling, then you will see how to cleanse your data of impurities and get it ready it for predictive modeling. You will also learn more about the best predictive modeling algorithms such as Linear Regression, Decision Trees, and Logistic Regression. Finally, you will see the best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world.

Machine Learning: End-to-End guide for Java developers. Data Analysis, Machine Learning, and Neural Networks simplified

Boštjan Kaluža, Krishna Choppella, Uday Kamath

Machine Learning is one of the core area of Artificial Intelligence where computers are trained to self-learn, grow, change, and develop on their own without being explicitly programmed. In this course, we cover how Java is employed to build powerful machine learning models to address the problems being faced in the world of Data Science. The course demonstrates complex data extraction and statistical analysis techniques supported by Java, applying various machine learning methods, exploring machine learning sub-domains, and exploring real-world use cases such as recommendation systems, fraud detection, natural language processing, and more, using Java programming. The course begins with an introduction to data science and basic data science tasks such as data collection, data cleaning, data analysis, and data visualization. The next section has a detailed overview of statistical techniques, covering machine learning, neural networks, and deep learning. The next couple of sections cover applying machine learning methods using Java to a variety of chores including classifying, predicting, forecasting, market basket analysis, clustering stream learning, active learning, semi-supervised learning, probabilistic graph modeling, text mining, and deep learning.The last section highlights real-world test cases such as performing activity recognition, developing image recognition, text classification, and anomaly detection. The course includes premium content from three of our most popular books:[*]Java for Data Science[*]Machine Learning in Java [*]Mastering Java Machine LearningOn completion of this course, you will understand various machine learning techniques, different machine learning java algorithms you can use to gain data insights, building data models to analyze larger complex data sets, and incubating applications using Java and machine learning algorithms in the field of artificial intelligence.

Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition

Giuseppe Bonaccorso

Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks.By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.

Managing Data Science. Effective strategies to manage data science projects and build a sustainable team

Kirill Dubovikov

Data science and machine learning can transform any organization and unlock new opportunities. However, employing the right management strategies is crucial to guide the solution from prototype to production. Traditional approaches often fail as they don't entirely meet the conditions and requirements necessary for current data science projects. In this book, you'll explore the right approach to data science project management, along with useful tips and best practices to guide you along the way. After understanding the practical applications of data science and artificial intelligence, you'll see how to incorporate them into your solutions. Next, you will go through the data science project life cycle, explore the common pitfalls encountered at each step, and learn how to avoid them. Any data science project requires a skilled team, and this book will offer the right advice for hiring and growing a data science team for your organization. Later, you'll be shown how to efficiently manage and improve your data science projects through the use of DevOps and ModelOps. By the end of this book, you will be well versed with various data science solutions and have gained practical insights into tackling the different challenges that you'll encounter on a daily basis.

Unity Virtual Reality Projects. Learn Virtual Reality by developing more than 10 engaging projects with Unity 2018 - Second Edition

Jonathan Linowes

Unity has become the leading platform for building virtual reality games, applications, and experiences for this new generation of consumer VR devices. Unity Virtual Reality Projects walks you through a series of hands-on tutorials and in-depth discussions on using the Unity game engine to develop VR applications. With its practical and project-based approach, this book will get you up to speed with the specifics of VR development in Unity. You will learn how to use Unity to develop VR applications that can be experienced with devices such as Oculus, Daydream, and Vive. Among the many topics and projects, you will explore gaze-based versus hand-controller input, world space UI canvases, locomotion and teleportation, software design patterns, 360-degree media, timeline animation, and multiplayer networking. You will learn about the Unity 3D game engine via the interactive Unity Editor, and you will also learn about C# programming. By the end of the book, you will be fully equipped to develop rich, interactive VR experiences using Unity.