Build fault-tolerant, robust, and distributed applications in Scala About This Book ? Understand and use the concepts of reactive programming to build distributed systems running on multiple nodes. ? Learn how reactive architecture reduces complexity throughout the development process. ? Get to grips with functional reactive programming and Reactive Microservices. Who This Book Is For This book is for Scala developers who would like to build fault-tolerant, scalable distributed systems. No knowledge of Reactive programming is required. What You Will Learn ? Understand the fundamental principles of Reactive and Functional programming ? Develop applications utilizing features of the Akka framework ? Explore techniques to integrate Scala, Akka, and Play together ? Learn about Reactive Streams with real-time use cases ? Develop Reactive Web Applications with Play, Scala, Akka, and Akka Streams ? Develop and deploy Reactive microservices using the Lagom framework and ConductR In Detail Reactive programming is a scalable, fast way to build applications, and one that helps us write code that is concise, clear, and readable. It can be used for many purposes such as GUIs, robotics, music, and others, and is central to many concurrent systems. This book will be your guide to getting started with Reactive programming in Scala. You will begin with the fundamental concepts of Reactive programming and gradually move on to working with asynchronous data streams. You will then start building an application using Akka Actors and extend it using the Play framework. You will also learn about reactive stream specifications, event sourcing techniques, and different methods to integrate Akka Streams into the Play Framework. This book will also take you one step forward by showing you the advantages of the Lagom framework while working with reactive microservices. You will also learn to scale applications using multi-node clusters and test, secure, and deploy your microservices to the cloud. By the end of the book, you will have gained the knowledge to build robust and distributed systems with Scala and Akka. Style and approach The book takes a pragmatic approach, showing you how to build a scalable distributed system using Scala and Akka.

Leverage the power of machine learning and Swift programming to build intelligent iOS applications with ease About This Book ? Implement effective machine learning solutions for your iOS applications ? Use Swift and Core ML to build and deploy popular machine learning models ? Develop neural networks for natural language processing and computer vision Who This Book Is For iOS developers who wish to create smarter iOS applications using the power of machine learning will find this book to be useful. This book will also benefit data science professionals who are interested in performing machine learning on mobile devices. Familiarity with Swift programming is all you need to get started with this book. What You Will Learn ? Learn rapid model prototyping with Python and Swift ? Deploy pre-trained models to iOS using Core ML ? Find hidden patterns in the data using unsupervised learning ? Get a deeper understanding of the clustering techniques ? Learn modern compact architectures of neural networks for iOS devices ? Train neural networks for image processing and natural language processing In Detail Machine learning as a field promises to bring increased intelligence to the software by helping us learn and analyse information efficiently and discover certain patterns that humans cannot. This book will be your guide as you embark on an exciting journey in machine learning using the popular Swift language. We’ll start with machine learning basics in the first part of the book to develop a lasting intuition about fundamental machine learning concepts. We explore various supervised and unsupervised statistical learning techniques and how to implement them in Swift, while the third section walks you through deep learning techniques with the help of typical real-world cases. In the last section, we will dive into some hard core topics such as model compression, GPU acceleration and provide some recommendations to avoid common mistakes during machine learning application development. By the end of the book, you'll be able to develop intelligent applications written in Swift that can learn for themselves. Style and approach A comprehensive guide that teaches how to implement machine learning apps for iOS from scratch

Build your defense against web attacks with Kali Linux, including command injection flaws, crypto implementation layers, and web application security holes About This Book ? Know how to set up your lab with Kali Linux ? Discover the core concepts of web penetration testing ? Get the tools and techniques you need with Kali Linux Who This Book Is For Since this book sets out to cover a large number of tools and security fields, it can work as an introduction to practical security skills for beginners in security. In addition, web programmers and also system administrators would benefit from this rigorous introduction to web penetration testing. Basic system administration skills are necessary, and the ability to read code is a must. What You Will Learn ? Learn how to set up your lab with Kali Linux ? Understand the core concepts of web penetration testing ? Get to know the tools and techniques you need to use with Kali Linux ? Identify the difference between hacking a web application and network hacking ? Expose vulnerabilities present in web servers and their applications using server-side attacks ? Understand the different techniques used to identify the flavor of web applications ? See standard attacks such as exploiting cross-site request forgery and cross-site *ing flaws ? Get an overview of the art of client-side attacks ? Explore automated attacks such as fuzzing web applications In Detail Web Penetration Testing with Kali Linux - Third Edition shows you how to set up a lab, helps you understand the nature and mechanics of attacking websites, and explains classical attacks in great depth. This edition is heavily updated for the latest Kali Linux changes and the most recent attacks. Kali Linux shines when it comes to client-side attacks and fuzzing in particular. From the start of the book, you'll be given a thorough grounding in the concepts of hacking and penetration testing, and you'll see the tools used in Kali Linux that relate to web application hacking. You'll gain a deep understanding of classicalSQL, command-injection flaws, and the many ways to exploit these flaws. Web penetration testing also needs a general overview of client-side attacks, which is rounded out by a long discussion of *ing and input validation flaws. There is also an important chapter on cryptographic implementation flaws, where we discuss the most recent problems with cryptographic layers in the networking stack. The importance of these attacks cannot be overstated, and defending against them is relevant to most internet users and, of course, penetration testers. At the end of the book, you'll use an automated technique called fuzzing to identify flaws in a web application. Finally, you'll gain an understanding of web application vulnerabilities and the ways they can be exploited using the tools in Kali Linux. Style and approach This step-by-step guide covers each topic with detailed practical examples. Every concept is explained with the help of illustrations using the tools available in Kali Linux.

Mike Driscoll takes you on a journey talking to a hall-of-fame list of truly remarkable Python experts. You’ll be inspired every time by their passion for the Python language, as they share with you their experiences, contributions, and careers in Python. About This Book ? Hear from these key Python thinkers about the current status of Python, and where it's heading in the future ? Listen to their close thoughts on significant Python topics, such as Python's role in scientific computing, and machine learning ? Understand the direction of Python, and what needs to change for Python 4 Who This Book Is For Python programmers and students interested in the way that Python is used – past and present – with useful anecdotes. It will also be of interest to those looking to gain insights from top programmers. What You Will Learn ? How successful programmers think ? The history of Python ? Insights into the minds of the Python core team ? Trends in Python programming In Detail Each of these twenty Python Interviews can inspire and refresh your relationship with Python and the people who make Python what it is today. Let these interviews spark your own creativity, and discover how you also have the ability to make your mark on a thriving tech community. This book invites you to immerse in the Python landscape, and let these remarkable programmers show you how you too can connect and share with Python programmers around the world. Learn from their opinions, enjoy their stories, and use their tech tips. ? Brett Cannon - former director of the PSF, Python core developer, led the migration to Python 3. ? Steve Holden - tireless Python promoter and former chairman and director of the PSF. ? Carol Willing - former director of the PSF and Python core developer, Project Jupyter Steering Council member. ? Nick Coghlan - founding member of the PSF and Python core developer. ? Jessica McKellar - former director of the PSF and Python activist. ? Marc-André Lemburg - Python core developer and founding member of the PSF. ? Glyph Lefkowitz - founder of Twisted and fellow of the PSF. ? Doug Hellmann - fellow of the PSF, creator of the Python Module of the Week blog, Python community member since 1998. ? Massimo Di Pierro - fellow of the PSF, data scientist and the inventor of web2py. ? Alex Martelli - fellow of the PSF and co-author of Python in a Nutshell. ? Barry Warsaw - fellow of the PSF, Python core developer since 1995, and original member of PythonLabs. ? Tarek Ziadé - founder of Afpy and author of Expert Python Programming. ? Sebastian Raschka - data scientist and author of Python Machine Learning. ? Wesley Chun - fellow of the PSF and author of the Core Python Programming books. ? Steven Lott - Python blogger and author of Python for Secret Agents. ? Oliver Schoenborn - author of Pypubsub and wxPython mailing list contributor. ? Al Sweigart - bestselling author and creator of the Python modules Pyperclip and PyAutoGUI. ? Luciano Ramalho - fellow of the PSF and the author of Fluent Python. ? Mike Bayer - fellow of the PSF, creator of open source libraries including SQLAlchemy. ? Jake Vanderplas - data scientist and author of Python Data Science Handbook. Style and approach This is a book of one-to-one interviews with leading Python programmers and luminaries in the field.

Develop and run efficient R *s and predictive models for SQL Server 2017 About This Book ? Learn how you can combine the power of R and SQL Server 2017 to build efficient, cost-effective data science solutions ? Leverage the capabilities of R Services to perform advanced analytics—from data exploration to predictive modeling ? A quick primer with practical examples to help you get up- and- running with SQL Server 2017 Machine Learning Services with R, as part of database solutions with continuous integration / continuous delivery. Who This Book Is For This book is for data analysts, data scientists, and database administrators with some or no experience in R but who are eager to easily deliver practical data science solutions in their day-to-day work (or future projects) using SQL Server. What You Will Learn ? Get an overview of SQL Server 2017 Machine Learning Services with R ? Manage SQL Server Machine Learning Services from installation to configuration and maintenance ? Handle and operationalize R code ? Explore RevoScaleR R algorithms and create predictive models ? Deploy, manage, and monitor database solutions with R ? Extend R with SQL Server 2017 features ? Explore the power of R for database administrators In Detail R Services was one of the most anticipated features in SQL Server 2016, improved significantly and rebranded as SQL Server 2017 Machine Learning Services. Prior to SQL Server 2016, many developers and data scientists were already using R to connect to SQL Server in siloed environments that left a lot to be desired, in order to do additional data analysis, superseding SSAS Data Mining or additional CLR programming functions. With R integrated within SQL Server 2017, these developers and data scientists can now benefit from its integrated, effective, efficient, and more streamlined analytics environment. This book gives you foundational knowledge and insights to help you understand SQL Server 2017 Machine Learning Services with R. First and foremost, the book provides practical examples on how to implement, use, and understand SQL Server and R integration in corporate environments, and also provides explanations and underlying motivations. It covers installing Machine Learning Services;maintaining, deploying, and managing code;and monitoring your services. Delving more deeply into predictive modeling and the RevoScaleR package, this book also provides insights into operationalizing code and exploring and visualizing data. To complete the journey, this book covers the new features in SQL Server 2017 and how they are compatible with R, amplifying their combined power. Style and approach This fast-paced guide will help data scientists and DBAs implement all new data science projects using SQL Server 2017 Machine Learning Services.

Your one step guide to learn all about AWS networking. About This Book ? Master your networking skills on Public Cloud. ? Gain hands-on experience of using Amazon VPC, Elastic Load Balancing, Direct Connect and other AWS products. ? Implement troubleshooting skills and best practices for security on AWS network. Who This Book Is For This book is targeted towards cloud architects, cloud solution providers, or any stakeholders dealing with networking on AWS Cloud. A prior idea of Amazon Web Services will be an added advantage. What You Will Learn ? Overview of all networking services available in AWS. ? Gain Work with load balance application across different regions. ? Learn auto scale instance based on the increase and decrease of the traffic. ? Deploy application in highly available and fault tolerant manner. ? Configure Route 53 for a web application. ? Troubleshooting tips and best practices at the end In Detail Amazon Web Services (AWS) dominates the public cloud market by a huge margin and it continues to be the first choice for many organizations. Networking has been an area of focus for all the leading cloud service providers. AWS has a suite of network-related products that help to perform network-related task in AWS. This book initially covers the basics of networking in AWS. Then we use AWS VPC to create an isolated virtual cloud for performing network-related tasks. We then provide an overview of AWS Direct Connect after taking a deep dive into scalability and load balancing using Auto scaling feature, Elastic Load Balancing, and Amazon Route S3. Toward the end of the book, we cover some troubleshooting tips and security best practices for your network. By the end of this book, you will have hands-on experience of working with network tasks on AWS. Style and approach A step by step practical guide that helps you use all networking services available in AWS effectively.

One stop guide to implementing award-winning, and cutting-edge CNN architectures About This Book ? Fast-paced guide with use cases and real-world examples to get well versed with CNN techniques ? Implement CNN models on image classification, transfer learning, Object Detection, Instance Segmentation, GANs and more ? Implement powerful use-cases like image captioning, reinforcement learning for hard attention, and recurrent attention models Who This Book Is For This book is for data scientists, machine learning and deep learning practitioners, Cognitive and Artificial Intelligence enthusiasts who want to move one step further in building Convolutional Neural Networks. Get hands-on experience with extreme datasets and different CNN architectures to build efficient and smart ConvNet models. Basic knowledge of deep learning concepts and Python programming language is expected. What You Will Learn ? From CNN basic building blocks to advanced concepts understand practical areas they can be applied to ? Build an image classifier CNN model to understand how different components interact with each other, and then learn how to optimize it ? Learn different algorithms that can be applied to Object Detection, and Instance Segmentation ? Learn advanced concepts like attention mechanisms for CNN to improve prediction accuracy ? Understand transfer learning and implement award-winning CNN architectures like AlexNet, VGG, GoogLeNet, ResNet and more ? Understand the working of generative adversarial networks and how it can create new, unseen images In Detail Convolutional Neural Network (CNN) is revolutionizing several application domains such as visual recognition systems, self-driving cars, medical discoveries, innovative eCommerce and more.You will learn to create innovative solutions around image and video analytics to solve complex machine learning and computer vision related problems and implement real-life CNN models. This book starts with an overview of deep neural networkswith the example of image classification and walks you through building your first CNN for human face detector. We will learn to use concepts like transfer learning with CNN, and Auto-Encoders to build very powerful models, even when not much of supervised training data of labeled images is available. Later we build upon the learning achieved to build advanced vision related algorithms for object detection, instance segmentation, generative adversarial networks, image captioning, attention mechanisms for vision, and recurrent models for vision. By the end of this book, you should be ready to implement advanced, effective and efficient CNN models at your professional project or personal initiatives by working on complex image and video datasets. Style and approach An easy to follow concise and illustrative guide explaining the core concepts of ConvNets to help you understand, implement and deploy your CNN models quickly.

Understand the ServiceNow *ing and build an efficient customized ServiceNow instance About This Book ? Customize your ServiceNow instance according to your organization’s needs ? Learn to work with inbuilt JavaScript APIs in ServiceNow ? Take your ServiceNow experience to the next level by learning to * Who This Book Is For This book is targeted toward ServiceNow administrators or anyone willing to learn inbuilt JavaScript APIs used to * and customize ServiceNow instances. Prior experience with ServiceNow is required. What You Will Learn ? Customize your ServiceNow instance according to your organization's needs ? Explore the ServiceNow-exposed JavaScript APIs and libraries ? Discover the method for using ServiceNow *ing functions ? Take your ServiceNow experience to the next level by understanding advanced *ing ? Learn to build, test, and debug custom applications ? Use your customized instance efficiently with the help of best practices In Detail Industry giants like RedHat and NetApp have adopted ServiceNow for their operational needs, and it is evolving as the number one platform choice for IT Service management. ServiceNow provides their clients with an add-on when it comes to baseline instances, where *ing can be used to customize and improve the performance of instances. It also provides inbuilt JavaScript API for *ing and improving your JavaScript instance. This book will initially cover the basics of ServiceNow *ing and the appropriate time to * in a ServiceNow environment. Then, we dig deeper into client-side and server-side *ing using JavaScipt API. We will also cover advance concepts like on-demand functions, * actions, and best practices. Mastering ServiceNow Scripting acts as an end-to-end guide for writing, testing, and debugging *s of ServiceNow. We cover update sets for moving customizations between ServiceNow instances, jelly *s for making custom pages, and best practices for all types of * in ServiceNow. By the end of this book, you will have hands-on experience in *ing ServiceNow using inbuilt JavaScript API. Style and approach The book will take a practical approach delving into different aspects of ServiceNow *ing to help you become a *ing master.

Leverage the power of Apple's Core ML to create smart iOS apps About This Book ? Explore the concepts of machine learning and Apple’s Core ML APIs ? Use Core ML to understand and transform images and videos ? Exploit the power of using CNN and RNN in iOS applications Who This Book Is For Machine Learning with Core ML is for you if you are an intermediate iOS developer interested in applying machine learning to your mobile apps. This book is also for those who are machine learning developers or deep learning practitioners who want to bring the power of neural networks in their iOS apps. Some exposure to machine learning concepts would be beneficial but not essential, as this book acts as a launchpad into the world of machine learning for developers. What You Will Learn ? Understand components of an ML project using algorithms, problems, and data ? Master Core ML by obtaining and importing machine learning model, and generate classes ? Prepare data for machine learning model and interpret results for optimized solutions ? Create and optimize custom layers for unsupported layers ? Apply CoreML to image and video data using CNN ? Learn the qualities of RNN to recognize sketches, and augment drawing ? Use Core ML transfer learning to execute style transfer on images In Detail Core ML is a popular framework by Apple, with APIs designed to support various machine learning tasks. It allows you to train your machine learning models and then integrate them into your iOS apps. Machine Learning with Core ML is a fun and practical guide that not only demystifies Core ML but also sheds light on machine learning. In this book, you’ll walk through realistic and interesting examples of machine learning in the context of mobile platforms (specifically iOS). You’ll learn to implement Core ML for visual-based applications using the principles of transfer learning and neural networks. Having got to grips with the basics, you’ll discover a series of seven examples, each providing a new use-case that uncovers how machine learning can be applied along with the related concepts. By the end of the book, you will have the skills required to put machine learning to work in their own applications, using the Core ML APIs Style and approach An easy-to-follow step by step guide which will help you get to grips with real world application of CoreML

Develop and deploy fully functional applications and microservices utilising Tomcat, Glassfish servers, Cloud and docker in Java EE 8 About This Book ? Explore the complete workflow of developing enterprise Java applications ? Develop microservices with Docker Container and deploy it in cloud ? Simplify Java EE application development Who This Book Is For If you are a Java developer with little or no experience in Java EE application development, or if you have experience in Java EE technology but are looking for tips to simplify and accelerate your development process, then this book is for you. What You Will Learn ? Set up Eclipse, Tomcat, and Glassfish servers for Java EE application development ? Use JSP, Servlet, JSF, and EJBs to create a user interface and write business logic ? Create Java EE database applications using JDBC and JPA ? Handle asynchronous messages using MDBs for better scalability ? Deploy and debug Java EE applications and create SOAP and REST web services ? Write unit tests and calculate code coverage ? Use Eclipse MAT (Memory Analysis Tool) to debug memory issues ? Create and deploy microservices In Detail Java EE is one of the most popular tools for enterprise application design and development. With recent changes to Java EE 8 specifications, Java EE application development has become a lot simpler with the new specifications, some of which compete with the existing specifications. This guide provides a complete overview of developing highly performant, robust and secure enterprise applications with Java EE with Eclipse. The book begins by exploring different Java EE technologies and how to use them (JSP, JSF, JPA, JDBC, EJB, and more), along with suitable technologies for different scenarios. You will learn how to set up the development environment for Java EE applications and understand Java EE specifications in detail, with an emphasis on examples. The book takes you through deployment of an application in Tomcat, GlassFish Servers, and also in the cloud. It goes beyond the basics and covers topics like debugging, testing, deployment, and securing your Java EE applications. You'll also get to know techniques to develop cloud-ready microservices in Java EE. Style and approach This guide takes a step-by-step approach to developing, testing, debugging, and troubleshooting Java EE applications, complete with examples and tips.

Create interactive cross-platform games with the Godot Engine 3.0 About This Book ? Learn the art of developing cross-platform games ? Leverage Godot’s node and scene system to design robust, reusable game objects ? Integrate Blender easily and efficiently with Godot to create powerful 3D games Who This Book Is For Godot Engine Game Development Projects is for both new users and experienced developers, who want to learn to make games using a modern game engine. Some prior programming experience is recommended. What You Will Learn ? Get started with the Godot game engine and editor ? Organize a game project ? Import graphical and audio assets ? Use Godot’s node and scene system to design robust, reusable game objects ? Write code in GDScript to capture input and build complex behaviors ? Implement user interfaces to display information ? Create visual effects to spice up your game ? Learn techniques that you can apply to your own game projects In Detail Godot Engine Game Development Projects is an introduction to the Godot game engine and its new 3.0 version. Godot 3.0 brings a large number of new features and capabilities that make it a strong alternative to expensive commercial game engines. For beginners, Godot offers a friendly way to learn game development techniques, while for experienced developers it is a powerful, customizable tool that can bring your visions to life. This book consists of five projects that will help developers achieve a sound understanding of the engine when it comes to building games. Game development is complex and involves a wide spectrum of knowledge and skills. This book can help you build on your foundation level skills by showing you how to create a number of small-scale game projects. Along the way, you will learn how Godot works and discover important game development techniques that you can apply to your projects. Using a straightforward, step-by-step approach and practical examples, the book will take you from the absolute basics through to sophisticated game physics, animations, and other techniques. Upon completing the final project, you will have a strong foundation for future success with Godot 3.0. Style and approach The book is divided into five parts; each covering a different small-game project using a straightforward, step-by-step approach and practical examples. The book will take readers from the absolute basics through sophisticated game physics, animation, and other techniques.

Complement Selenium with useful additions that fit seamlessly into the rich and well-crafted API that Selenium offers About This Book ? Understand the power, simplicity, and limitations of the core Selenium framework ? Write clear, readable, and reliable tests that perform complex test automation tasks ? Work with ChromeDriver and GeckoDriver in headless mode Who This Book Is For If you are a software tester or a developer with working experience in Selenium and competency with Java, who is interested in automation and are looking forward to taking the next step in their learning journey, then this is the book for you. What You Will Learn ? Provide fast, useful feedback with screenshots ? Create extensible, well-composed page objects ? Utilize ChromeDriver and GeckoDriver in headless mode ? Leverage the full power of Advanced User Interactions APIs ? Use JavascriptExecutor to execute JavaScript snippets in the browser through Selenium ? Build user interaction into your test script using JavascriptExecutor ? Learn the basics of working with Appium In Detail The second edition of Mastering Selenium 3.0 WebDriver starts by showing you how to build your own Selenium framework with Maven. You'll then look at how you can solve the difficult problems that you will undoubtedly come across as you start using Selenium in an enterprise environment and learn how to produce the right feedback when failing. Next, you’ll explore common exceptions that you will come across as you use Selenium, the root causes of these exceptions, and how to fix them. Along the way, you’ll use Advanced User Interactions APIs, running any JavaScript you need through Selenium; and learn how to quickly spin up a Selenium Grid using Docker containers. In the concluding chapters, you‘ll work through a series of scenarios that demonstrate how to extend Selenium to work with external libraries and applications so that you can be sure you are using the right tool for the job. Style and approach This book is a pragmatic guide that takes you through the process of creating a test framework with Selenium 3. It then shows you how you can extend this framework to overcome common obstacles that you will come across whilst using Selenium.

Understand malware analysis and its practical implementation About This Book ? Explore the key concepts of malware analysis and memory forensics using real-world examples ? Learn the art of detecting, analyzing, and investigating malware threats ? Understand adversary tactics and techniques Who This Book Is For This book is for incident responders, cyber-security investigators, system administrators, malware analyst, forensic practitioners, student, or curious security professionals interested in learning malware analysis and memory forensics. Knowledge of programming languages such as C and Python is helpful but is not mandatory. If you have written few lines of code and have a basic understanding of programming concepts, you’ll be able to get most out of this book. What You Will Learn ? Create a safe and isolated lab environment for malware analysis ? Extract the metadata associated with malware ? Determine malware's interaction with the system ? Perform code analysis using IDA Pro and x64dbg ? Reverse-engineer various malware functionalities ? Reverse engineer and decode common encoding/encryption algorithms ? Perform different code injection and hooking techniques ? Investigate and hunt malware using memory forensics In Detail Malware analysis and memory forensics are powerful analysis and investigation techniques used in reverse engineering, digital forensics, and incident response. With adversaries becoming sophisticated and carrying out advanced malware attacks on critical infrastructures, data centers, and private and public organizations, detecting, responding to, and investigating such intrusions is critical to information security professionals. Malware analysis and memory forensics have become must-have skills to fight advanced malware, targeted attacks, and security breaches. This book teaches you the concepts, techniques, and tools to understand the behavior and characteristics of malware through malware analysis. It also teaches you techniques to investigate and hunt malware using memory forensics. This book introduces you to the basics of malware analysis, and then gradually progresses into the more advanced concepts of code analysis and memory forensics. It uses real-world malware samples, infected memory images, and visual diagrams to help you gain a better understanding of the subject and to equip you with the skills required to analyze, investigate, and respond to malware-related incidents. Style and approach The book takes the reader through all the concepts, techniques and tools to understand the behavior and characteristics of malware by using malware analysis and it also teaches the techniques to investigate and hunt malware using memory forensics.

Build a solid foundation in coding by utilizing the language and its core characteristics About This Book ? Leverage the features of Python programming through easy-to-follow examples ? Develop a strong set of programming skills that can be applied on all platforms ? Create GUIs and data science-based applications Who This Book Is For Learn Python Programming is for individuals with relatively little experience in coding or Python. It's also ideal for aspiring programmers who need to write scripts or programs to accomplish tasks. The book takes you all the way to creating a full-fledged application. What You Will Learn ? Get Python up and running on Windows, Mac, and Linux ? Grasp fundamental concepts of coding using data structures and control flow ? Write elegant, reusable, and efficient code in any situation ? Understand when to use the functional or object-oriented programming (OOP) approach ? Walk through the basics of security and concurrent/asynchronous programming ? Create bulletproof, reliable software by writing tests ? Explore examples of GUIs, scripting, and data science In Detail Learn Python Programming creates a foundation for those who are interested in developing their skills in Python programming. The book starts with the fundamentals of programming with Python and ends by exploring different topics such as GUIs and real-world apps. You will begin by exploring the foundations of and fundamental topics on Python and learn to manipulate them. Then, you'll explore different programming paradigms that will allow you to find the best approach to a situation, and you’ll also understand how to carry out performance optimization as well as effective debugging. As you make your way through the chapters, you'll control the flow of a program, and persist and utilize an interchange format to exchange data. You'll also walk through cryptographic services in Python and understand secure tokens. Throughout, the book covers various types of applications, and it concludes with building real-world applications based on all the concepts that you learned. By the end of the book, you'll have a proper understanding of the Python language and a solid grasp on how to work with data. You'll know how to quickly build a website and harness the power of Python's renowned data science libraries. Style and approach This easy-to-follow guide will take you from novice to proficient at a comfortable pace, using a lot of simple yet effective examples.

Build and deploy powerful neural network models using the latest Java deep learning libraries About This Book ? Understand DL with Java by implementing real-world projects ? Master implementations of various ANN models and build your own DL systems ? Develop applications using NLP, image classification, RL, and GPU processing Who This Book Is For If you are a data scientist, machine learning professional, or deep learning practitioner keen to expand your knowledge by delving into the practical aspects of deep learning with Java, then this book is what you need! Get ready to build advanced deep learning models to carry out complex numerical computations. Some basic understanding of machine learning concepts and a working knowledge of Java are required. What You Will Learn ? Master deep learning and neural network architectures ? Build real-life applications covering image classification, object detection, online trading, transfer learning, and multimedia analytics using DL4J and open-source APIs ? Train ML agents to learn from data using deep reinforcement learning ? Use factorization machines for advanced movie recommendations ? Train DL models on distributed GPUs for faster deep learning with Spark and DL4J ? Ease your learning experience through 69 FAQs In Detail Java is one of the most widely used programming languages. With the rise of deep learning, it has become a popular choice of tool among data scientists and machine learning experts. Java Deep Learning Projects starts with an overview of deep learning concepts and then delves into advanced projects. You will see how to build several projects using different deep neural network architectures such as multilayer perceptrons, Deep Belief Networks, CNN, LSTM, and Factorization Machines. You will get acquainted with popular deep and machine learning libraries for Java such as Deeplearning4j, Spark ML, and RankSys and you’ll be able to use their features to build and deploy projects on distributed computing environments. You will then explore advanced domains such as transfer learning and deep reinforcement learning using the Java ecosystem, covering various real-world domains such as healthcare, NLP, image classification, and multimedia analytics with an easy-to-follow approach. Expert reviews and tips will follow every project to give you insights and hacks. By the end of this book, you will have stepped up your expertise when it comes to deep learning in Java, taking it beyond theory and be able to build your own advanced deep learning systems. Style and approach A unique, learn-as-you-do approach, as the reader builds on his understanding of deep learning with Java progressively with each project. This book is designed in such a way that implementing each project will empower you with a unique skill set, and enable you to implement the next project more confidently.

Learn steps and tasks to help a NetSuite administrator perform both his daily and monthly tasks efficiently. Advance his expertise to become NetSuite leader without having to spend time and money on corporate trainings. About This Book ? Understand the business considerations and implementation of the NetSuite ERP ? Gain a deep knowledge of enterprise security, data management, process automation, and analytics ? Learn techniques to sail through system maintenance while ensuring accuracy and to practically troubleshoot issues Who This Book Is For This book is for administrators, consultants, and Project Managers who would like to improve their skills in the areas of configuration and system management. Basic experience implementing NetSuite is assumed. What You Will Learn ? Provide executives with meaningful insights into the business ? A Framework to streamline the implementation of new and existing features ? Leverage built-in tools to optimize your efficiency and effectiveness ? Test configuration to check the implementation of role-specific permissions ? Understand how to optimize the amount of data to be shared with users ? Import data like new leads and employ current data like pricing updates ? Perform on-going maintenance and troubleshoot issues In Detail NetSuite ERP is a complete, scalable cloud ERP solution targeted at fast-growing, mid-sized businesses and large enterprises. It's the smartly executed combination of financial management operations and built-in business intelligence, which enables companies to make data-driven and well-informed decisions. This book will help administrators become expert enough to be seen as the NetSuite leader at their company and to be able to advise department heads on specific processes, and strategic decisions. We start with an overview of ERP and NetSuite ERP, before going on to explain the built-in features to show the breadth of NetSuite ERP's product and its ease of use. We then discuss business aspects, focusing on the most important processes in NetSuite. Then you'll understand the implementation aspects that are generic enough to cover all the features. The focus then shifts to specific skills that you will need to administer for any system, such as roles, permissions, customization, and data imports. Moving on, you'll learn how to centralize the creation of search templates and give users the tools to pivot the data and expose it to the user in useful ways, such as on the dashboard. The book ends with checklists providing actionable steps that you as an administrator can take to do your job and support the application through new releases and troubleshooting problems. Style and approach A slow and steady introduction of topics from reports through searches with aim to enable the administrator to gain a holistic view of the NetSuite product.

Work with Python and powerful open source tools such as Gensim and spaCy to perform modern text analysis, natural language processing, and computational linguistics algorithms. About This Book ? Discover the open source Python text analysis ecosystem, using spaCy, Gensim, scikit-learn, and Keras ? Hands-on text analysis with Python, featuring natural language processing and computational linguistics algorithms ? Learn deep learning techniques for text analysis Who This Book Is For This book is for you if you want to dive in, hands-first, into the interesting world of text analysis and NLP, and you're ready to work with the rich Python ecosystem of tools and datasets waiting for you! What You Will Learn ? Why text analysis is important in our modern age ? Understand NLP terminology and get to know the Python tools and datasets ? Learn how to pre-process and clean textual data ? Convert textual data into vector space representations ? Using spaCy to process text ? Train your own NLP models for computational linguistics ? Use statistical learning and Topic Modeling algorithms for text, using Gensim and scikit-learn ? Employ deep learning techniques for text analysis using Keras In Detail Modern text analysis is now very accessible using Python and open source tools, so discover how you can now perform modern text analysis in this era of textual data. This book shows you how to use natural language processing, and computational linguistics algorithms, to make inferences and gain insights about data you have. These algorithms are based on statistical machine learning and artificial intelligence techniques. The tools to work with these algorithms are available to you right now - with Python, and tools like Gensim and spaCy. You'll start by learning about data cleaning, and then how to perform computational linguistics from first concepts. You're then ready to explore the more sophisticated areas of statistical NLP and deep learning using Python, with realistic language and text samples. You'll learn to tag, parse, and model text using the best tools. You'll gain hands-on knowledge of the best frameworks to use, and you'll know when to choose a tool like Gensim for topic models, and when to work with Keras for deep learning. This book balances theory and practical hands-on examples, so you can learn about and conduct your own natural language processing projects and computational linguistics. You'll discover the rich ecosystem of Python tools you have available to conduct NLP - and enter the interesting world of modern text analysis. Style and approach The book teaches NLP from the angle of a practitioner as well as that of a student. This is a tad unusual, but given the enormous speed at which new algorithms and approaches travel from scientific beginnings to industrial implementation, first principles can be clarified with the help of entirely practical examples.

Get to grips with the most popular Python packages that make data analysis possible About This Book ? Explore the tools you need to become a data analyst ? Discover practical examples to help you grasp data processing concepts ? Walk through hierarchical indexing and grouping for data analysis Who This Book Is For Hands-On Data Analysis with NumPy and Pandas is for you if you are a Python developer and want to take your first steps into the world of data analysis. No previous experience of data analysis is required to enjoy this book. What You Will Learn ? Understand how to install and manage Anaconda ? Read, sort, and map data using NumPy and pandas ? Find out how to create and slice data arrays using NumPy ? Discover how to subset your DataFrames using pandas ? Handle missing data in a pandas DataFrame ? Explore hierarchical indexing and plotting with pandas In Detail Python, a multi-paradigm programming language, has become the language of choice for data scientists for visualization, data analysis, and machine learning. Hands-On Data Analysis with NumPy and Pandas starts by guiding you in setting up the right environment for data analysis with Python, along with helping you install the correct Python distribution. In addition to this, you will work with the Jupyter notebook and set up a database. Once you have covered Jupyter, you will dig deep into Python’s NumPy package, a powerful extension with advanced mathematical functions. You will then move on to creating NumPy arrays and employing different array methods and functions. You will explore Python’s pandas extension which will help you get to grips with data mining and learn to subset your data. Last but not the least you will grasp how to manage your datasets by sorting and ranking them. By the end of this book, you will have learned to index and group your data for sophisticated data analysis and manipulation. Style and approach A step-by-step approach, taking you through the different concepts and features of Data Analysis using Python libraries and tools.

Get up and running with the fundamentals of Amazon Alexa and build exciting IoT projects About This Book ? Gain hands-on experience of working with Amazon Echo and Alexa ? Build exciting IoT projects using Amazon Echo ? Learn about voice-enabled smart devices Who This Book Is For Alexa Skills Projects is for individuals who want to have a deep understanding of the underlying technology that drives Amazon Echo and Alexa, and how it can be integrated with the Internet of Things to develop hands-on projects. What You Will Learn ? Understand how Amazon Echo is already being used in various domains ? Discover how an Alexa Skill is architected ? Get a clear understanding of how some of the most popular Alexa Skills work ? Design Alexa Skills for specific purposes and interact with Amazon Echo to execute them ? Gain experience of programming for Amazon Echo ? Explore future applications of Amazon Echo and other voice-activated devices In Detail Amazon Echo is a smart speaker developed by Amazon, which connects to Amazon’s Alexa Voice Service and is entirely controlled by voice commands. Amazon Echo is currently being used for a variety of purposes such as home automation, asking generic queries, and even ordering a cab or pizza. Alexa Skills Projects starts with a basic introduction to Amazon Alexa and Echo. You will then deep dive into Alexa Programming concepts such as Intents, Slots, Lambdas and maintaining your skill’s state using DynamoDB. You will get a clear understanding of how some of the most popular Alexa Skills work, and gain experience of working with real-world Amazon Echo applications. In the concluding chapters, you will explore the future of voice-enabled applications and their coverage with respect to the Internet of Things. By the end of the book, you will have learned to design Alexa Skills for specific purposes and interact with Amazon Echo to execute these skills. Style and approach A practical guide filled with real world examples that will help you understand the process of creating Alexa Skills from scratch and it's real world applications.

Discover techniques and tools for building serverless applications with AWS Lambda About This Book ? Learn to write, run, and deploy Lambda functions in the AWS cloud ? Make the most of AWS Lambda functions to build scalable and cost-efficient systems ? A practical guide to developing serverless services and applications in Node.js, Java, Python, and C# Who This Book Is For This book is primarily for IT architects and developers who want to build scalable systems and deploy serverless applications with AWS Lambda. No prior knowledge of AWS is necessary. What You Will Learn ? Understand the fundamental concepts of AWS Lambda ? Get to grips with the Serverless Framework and how to create a serverless project ? Testing and debugging Lambda functions ? Create a stateful, serverless backend with DynamoDB ? Program AWS Lambda with Java, Python, and C# ? Program a lambda function with Node.js In Detail AWS Lambda is a part of AWS that lets you run your code without provisioning or managing servers. This enables you to deploy applications and backend services that operate with no upfront cost. This book gets you up to speed on how to build scalable systems and deploy serverless applications with AWS Lambda. The book starts with the fundamental concepts of AWS Lambda, and then teaches you how to combine your applications with other AWS services, such as AmazonAPI Gateway and DynamoDB. This book will also give a quick walk through on how to use the Serverless Framework to build larger applications that can structure code or autogenerate boilerplate code that can be used to get started quickly for increased productivity. Toward the end of the book, you will learn how to write, run, and test Lambda functions using Node.js, Java, Python, and C#. Style and approach This book will provide clear instructions that introduce the viewer to programming AWS Lambda with Node.js, Java, Python, and C#. Moreover, readers will learn how to deploy and test Lambda functions, and how to set up and use the serverless framework.

Explore the various packages in Julia that support image processing and build neural networks for video processing and object tracking. About This Book ? Build a full-fledged image processing application using JuliaImages ? Perform basic to advanced image and video stream processing with Julia's APIs ? Understand and optimize various features of OpenCV with easy examples Who This Book Is For Hands-On Computer Vision with Julia is for Julia developers who are interested in learning how to perform image processing and want to explore the field of computer vision. Basic knowledge of Julia will help you understand the concepts more effectively. What You Will Learn ? Analyze image metadata and identify critical data using JuliaImages ? Apply filters and improve image quality and color schemes ? Extract 2D features for image comparison using JuliaFeatures ? Cluster and classify images with KNN/SVM machine learning algorithms ? Recognize text in an image using the Tesseract library ? Use OpenCV to recognize specific objects or faces in images and videos ? Build neural network and classify images with MXNet In Detail Hands-On Computer Vision with Julia is a thorough guide for developers who want to get started with building computer vision applications using Julia. Julia is well suited to image processing because it’s easy to use and lets you write easy-to-compile and efficient machine code. This book begins by introducing you to Julia's image processing libraries such as Images.jl and ImageCore.jl. You’ll get to grips with analyzing and transforming images using JuliaImages; some of the techniques discussed include enhancing and adjusting images. As you make your way through the chapters, you’ll learn how to classify images, cluster them, and apply neural networks to solve computer vision problems. In the concluding chapters, you will explore OpenCV applications to perform real-time computer vision analysis, for example, face detection and object tracking. You will also understand Julia's interaction with Tesseract to perform optical character recognition and build an application that brings together all the techniques we introduced previously to consolidate the concepts learned. By end of the book, you will have understood how to utilize various Julia packages and a few open source libraries such as Tesseract and OpenCV to solve computer vision problems with ease. Style and approach Readers will be taken through various packages that support image processing in Julia, and will also tap into open-source libraries such as Open CV and Tesseract to find the optimum solution to problems encountered in computer vision.