Serverless Design Patterns and Best Practices. Build, secure, and deploy enterprise ready serverless applications with AWS to improve developer productivity

Brian Zambrano

Serverless applications handle many problems that developers face when running systems and servers. The serverless pay-per-invocation model can also result in drastic cost savings, contributing to its popularity. While it's simple to create a basic serverless application, it's critical to structure your software correctly to ensure it continues to succeed as it grows. Serverless Design Patterns and Best Practices presents patterns that can be adapted to run in a serverless environment. You will learn how to develop applications that are scalable, fault tolerant, and well-tested. The book begins with an introduction to the different design pattern categories available for serverless applications. You will learn thetrade-offs between GraphQL and REST and how they fare regarding overall application design in a serverless ecosystem. The book will also show you how to migrate an existing API to a serverless backend using AWS API Gateway. You will learn how to build event-driven applications using queuing and streaming systems, such as AWS Simple Queuing Service (SQS) and AWS Kinesis. Patterns for data-intensive serverless application are also explained, including the lambda architecture and MapReduce. This book will equip you with the knowledge and skills you need to develop scalable and resilient serverless applications confidently.

Tableau 10 Complete Reference. Transform your business with rich data visualizations and interactive dashboards with Tableau 10

Joshua N. Milligan, Tristan Guillevin

Graphical presentation of data enables us to easily understand complex data sets. Tableau 10 Complete Reference provides easy-to-follow recipes with several use cases and real-world business scenarios to get you up and running with Tableau 10.This Learning Path begins with the history of data visualization and its importance in today's businesses. You'll also be introduced to Tableau - how to connect, clean, and analyze data in this visual analytics software. Then, you'll learn how to apply what you've learned by creating some simple calculations in Tableau and using Table Calculations to help drive greater analysis from your data. Next, you'll explore different advanced chart types in Tableau. These chart types require you to have some understanding of the Tableau interface and understand basic calculations. You’ll study in detail all dashboard techniques and best practices. A number of recipes specifically for geospatial visualization, analytics, and data preparation are also covered. Last but not least, you'll learn about the power of storytelling through the creation of interactive dashboards in Tableau. Through this Learning Path, you will gain confidence and competence to analyze and communicate data and insights more efficiently and effectively by creating compelling interactive charts, dashboards, and stories in Tableau.This Learning Path includes content from the following Packt products:• Learning Tableau 10 - Second Edition by Joshua N. Milligan• Getting Started with Tableau 2018.x by Tristan Guillevin

Learning Rust. A comprehensive guide to writing Rust applications

Paul Johnson, Vesa Kaihlavirta

Rust is a highly concurrent and high performance language that focuses on safety and speed, memory management, and writing clean code. It also guarantees thread safety, and its aim is to improve the performance of existing applications. Its potential is shown by the fact that it has been backed by Mozilla to solve the critical problem of concurrency.Learning Rust will teach you to build concurrent, fast, and robust applications. From learning the basic syntax to writing complex functions, this book will is your one stop guide to get up to speed with the fundamentals of Rust programming. We will cover the essentials of the language, including variables, procedures, output, compiling, installing, and memory handling. You will learn how to write object-oriented code, work with generics, conduct pattern matching, and build macros. You will get to know how to communicate with users and other services, as well as getting to grips with generics, scoping, and more advanced conditions. You will also discover how to extend the compilation unit in Rust. By the end of this book, you will be able to create a complex application in Rust to move forward with.

Beginning Data Science with Python and Jupyter. Use powerful industry-standard tools within Jupyter and the Python ecosystem to unlock new, actionable insights from your data

Alex Galea

Get to grips with the skills you need for entry-level data science in this hands-on Python and Jupyter course. You'll learn about some of the most commonly used libraries that are part of the Anaconda distribution, and then explore machine learning models with real datasets to give you the skills and exposure you need for the real world. We'll finish up by showing you how easy it can be to scrape and gather your own data from the open web, so that you can apply your new skills in an actionable context.

Learning Apache Spark 2. A beginner’s guide to real-time Big Data processing using the Apache Spark framework

Muhammad Asif Abbasi

Apache Spark has seen an unprecedented growth in terms of its adoption over the last few years, mainly because of its speed, diversity and real-time data processing capabilities. It has quickly become the preferred choice of tool for many Big Data professionals looking to find quick insights from large chunks of data. This book introduces you to the Apache Spark framework, and familiarizes you with all the latest features and capabilities introduced in Spark 2.Starting with a detailed introduction to Spark’s architecture and the installation procedure, this book covers everything you need to know about the Spark framework in the most practical manner. You will learn how to perform the basic ETL activities using Spark, and work with different components of Spark such as Spark SQL, as well as the Dataset and DataFrame APIs for manipulating your data. Then, you will perform machine learning using Spark MLlib, as well as perform streaming analytics and graph processing using the Spark Streaming and GraphX modules respectively. The book also gives special emphasis on deploying your Spark models, and how they can be operated in a clustered mode.During the course of the book, you will come across implementations of different real-world use-cases and examples, giving you the hands-on knowledge you need to use Apache Spark in the best possible manner.

Learning OpenStack Networking. Build a solid foundation in virtual networking technologies for OpenStack-based clouds - Third Edition

James Denton

OpenStack Networking is a pluggable, scalable, and API-driven system to manage physical and virtual networking resources in an OpenStack-based cloud. Like other core OpenStack components, OpenStack Networking can be used by administrators and users to increase the value and maximize the use of existing datacenter resources. This third edition of Learning OpenStack Networking walks you through the installation of OpenStack and provides you with a foundation that can be used to build a scalable and production-ready OpenStack cloud.In the initial chapters, you will review the physical network requirements and architectures necessary for an OpenStack environment that provide core cloud functionality. Then, you’ll move through the installation of the new release of OpenStack using packages from the Ubuntu repository. An overview of Neutron networking foundational concepts, including networks, subnets, and ports will segue into advanced topics such as security groups, distributed virtual routers, virtual load balancers, and VLAN tagging within instances.By the end of this book, you will have built a network infrastructure for your cloud using OpenStack Neutron.

Neural Network Projects with Python. The ultimate guide to using Python to explore the true power of neural networks through six projects

James Loy

Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them.It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch.By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.

R Machine Learning Projects. Implement supervised, unsupervised, and reinforcement learning techniques using R 3.5

Dr. Sunil Kumar Chinnamgari

R is one of the most popular languages when it comes to performing computational statistics (statistical computing) easily and exploring the mathematical side of machine learning. With this book, you will leverage the R ecosystem to build efficient machine learning applications that carry out intelligent tasks within your organization.This book will help you test your knowledge and skills, guiding you on how to build easily through to complex machine learning projects. You will first learn how to build powerful machine learning models with ensembles to predict employee attrition. Next, you’ll implement a joke recommendation engine and learn how to perform sentiment analysis on Amazon reviews. You’ll also explore different clustering techniques to segment customers using wholesale data. In addition to this, the book will get you acquainted with credit card fraud detection using autoencoders, and reinforcement learning to make predictions and win on a casino slot machine.By the end of the book, you will be equipped to confidently perform complex tasks to build research and commercial projects for automated operations.

Microsoft Power BI Complete Reference. Bring your data to life with the powerful features of Microsoft Power BI

Devin Knight, Brian Knight, Mitchell Pearson, Manuel Quintana, ...

Microsoft Power BI Complete Reference Guide gets you started with business intelligence by showing you how to install the Power BI toolset, design effective data models, and build basic dashboards and visualizations that make your data come to life.In this Learning Path, you will learn to create powerful interactive reports by visualizing your data and learn visualization styles, tips and tricks to bring your data to life. You will be able to administer your organization's Power BI environment to create and share dashboards. You will also be able to streamline deployment by implementing security and regular data refreshes.Next, you will delve deeper into the nuances of Power BI and handling projects. You will get acquainted with planning a Power BI project, development, and distribution of content, and deployment. You will learn to connect and extract data from various sources to create robust datasets, reports, and dashboards. Additionally, you will learn how to format reports and apply custom visuals, animation and analytics to further refine your data.By the end of this Learning Path, you will learn to implement the various Power BI tools such as on-premises gateway together along with staging and securely distributing content via apps. This Learning Path includes content from the following Packt products:• Microsoft Power BI Quick Start Guide by Devin Knight et al. • Mastering Microsoft Power BI by Brett Powell

Java: High-Performance Apps with Java 9. Boost your application’s performance with the new features of Java 9

Mayur Ramgir

Java 9 which is one of the most popular application development languages. The latest released version Java 9 comes with a host of new features and new APIs with lots of ready to use components to build efficient and scalable applications. Streams, parallel and asynchronous processing, multithreading, JSON support, reactive programming, and microservices comprise the hallmark of modern programming and are now fully integrated into the JDK. This book focuses on providing quick, practical solutions to enhance your application's performance. You will explore the new features, APIs, and various tools added in Java 9 that help to speed up the development process. You will learn about jshell, Ahead-of-Time (AOT) compilation, and the basic threads related topics including sizing and synchronization. You will also explore various strategies for building microservices including container-less, self-contained, and in-container. This book is ideal for developers who would like to build reliable and high-performance applications with Java. This book is embedded with useful assessments that will help you revise the concepts you have learned in this book. This book is repurposed for this specific learning experience from material from Packt's Java 9 High Performance by Mayur Ramgir and Nick Samoylov

Modular Programming in Java 9. Build large scale applications using Java modularity and Project Jigsaw

Koushik Srinivas Kothagal

The Java 9 module system is an important addition to the language that affects the way we design, write, and organize code and libraries in Java. It provides a new way to achieve maintainable code by the encapsulation of Java types, as well as a way to write better libraries that have clear interfaces. Effectively using the module system requires an understanding of how modules work and what the best practices of creating modules are.This book will give you step-by-step instructions to create new modules as well as migrate code from earlier versions of Java to the Java 9 module system. You'll be working on a fully modular sample application and add features to it as you learn about Java modules. You'll learn how to create module definitions, setup inter-module dependencies, and use the built-in modules from the modular JDK. You will also learn about module resolution and how to use jlink to generate custom runtime images.We will end our journey by taking a look at the road ahead. You will learn some powerful best practices that will help you as you start building modular applications. You will also learn how to upgrade an existing Java 8 codebase to Java 9, handle issues with libraries, and how to test Java 9 applications.

Professional SQL Server High Availability and Disaster Recovery. Implement tried-and-true high availability and disaster recovery solutions with SQL Server

Ahmad Osama

Professional SQL Server High Availability and Disaster Recovery explains the high availability and disaster recovery technologies available in SQL Server: Replication, AlwaysOn, and Log Shipping. You’ll learn what they are, how to monitor them, and how to troubleshoot any related problems. You will be introduced to the availability groups of AlwaysOn and learn how to configure them to extend your database mirroring. Through this book, you will be able to explore the technical implementations of high availability and disaster recovery technologies that you can use when you create a highly available infrastructure, including hybrid topologies. Note that this course does not cover SQL Server Failover Cluster Installation with shared storage.By the end of the book, you’ll be equipped with all that you need to know to develop robust and high performance infrastructure.

Troubleshooting Docker. Develop, test, automate, and deploy production-ready Docker containers

Vaibhav Kohli, Rajdeep Dua, John Wooten

You?re pro Docker? You?ve read all about orchestration with Docker in books? Now learn how to troubleshoot Docker in practice. Gain all the tools to safely see Docker in action with this 2017 book.

Building Bots with Microsoft Bot Framework. Creating intelligent conversational interfaces

Kishore Gaddam

Bots help users to use the language as a UI and interact with the applications from any platform. This book teaches you how to develop real-world bots using Microsoft Bot Framework.The book starts with setting up the Microsoft Bot Framework development environment and emulator, and moves on to building the first bot using Connector and Builder SDK. Explore how to register, connect, test, and publish your bot to the Slack, Skype, and Facebook Messenger platforms. Throughout this book, you will build different types of bots from simple to complex, such as a weather bot, a natural speech and intent processing bot, an Interactive Voice Response (IVR) bot for a bank, a facial expression recognition bot, and more from scratch. These bots were designed and developed to teach you concepts such as text detection, implementing LUIS dialogs, Cortana Intelligence Services, third-party authentication, Rich Text format, Bot State Service, and microServices so you can practice working with the standard development tools such as Visual Studio, Bot Emulator, and Azure.

Machine Learning with R Quick Start Guide. A beginner's guide to implementing machine learning techniques from scratch using R 3.5

Iván Pastor Sanz

Machine Learning with R Quick Start Guide takes you on a data-driven journey that starts with the very basics of R and machine learning. It gradually builds upon core concepts so you can handle the varied complexities of data and understand each stage of the machine learning pipeline.From data collection to implementing Natural Language Processing (NLP), this book covers it all. You will implement key machine learning algorithms to understand how they are used to build smart models. You will cover tasks such as clustering, logistic regressions, random forests, support vector machines, and more. Furthermore, you will also look at more advanced aspects such as training neural networks and topic modeling.By the end of the book, you will be able to apply the concepts of machine learning, deal with data-related problems, and solve them using the powerful yet simple language that is R.

Hands-On GPU Programming with Python and CUDA. Explore high-performance parallel computing with CUDA

Dr. Brian Tuomanen

Hands-On GPU Programming with Python and CUDA hits the ground running: you’ll start by learning how to apply Amdahl’s Law, use a code profiler to identify bottlenecks in your Python code, and set up an appropriate GPU programming environment. You’ll then see how to “query” the GPU’s features and copy arrays of data to and from the GPU’s own memory.As you make your way through the book, you’ll launch code directly onto the GPU and write full blown GPU kernels and device functions in CUDA C. You’ll get to grips with profiling GPU code effectively and fully test and debug your code using Nsight IDE. Next, you’ll explore some of the more well-known NVIDIA libraries, such as cuFFT and cuBLAS.With a solid background in place, you will now apply your new-found knowledge to develop your very own GPU-based deep neural network from scratch. You’ll then explore advanced topics, such as warp shuffling, dynamic parallelism, and PTX assembly. In the final chapter, you’ll see some topics and applications related to GPU programming that you may wish to pursue, including AI, graphics, and blockchain.By the end of this book, you will be able to apply GPU programming to problems related to data science and high-performance computing.