Create end-to-end systems that can power robots with artificial vision and deep learning techniques Key Features * Study ROS, the main development framework for robotics, in detail * Learn all about convolutional neural networks, recurrent neural networks, and robotics * Create a chatbot to interact with the robot Book Description Artificial Vision and Language Processing for Robotics begins by discussing the theory behind robots. You'll compare different methods used to work with robots and explore computer vision, its algorithms, and limits. You'll then learn how to control the robot with natural language processing commands. You'll study Word2Vec and GloVe embedding techniques, non-numeric data, recurrent neural network (RNNs), and their advanced models. You'll create a simple Word2Vec model with Keras, as well as build a convolutional neural network (CNN) and improve it with data augmentation and transfer learning. You'll study the ROS and build a conversational agent to manage your robot. You'll also integrate your agent with the ROS and convert an image to text and text to speech. You'll learn to build an object recognition system using a video. By the end of this book, you'll have the skills you need to build a functional application that can integrate with a ROS to extract useful information about your environment. What you will learn * Explore the ROS and build a basic robotic system * Understand the architecture of neural networks * Identify conversation intents with NLP techniques * Learn and use the embedding with Word2Vec and GloVe * Build a basic CNN and improve it using generative models * Use deep learning to implement artificial intelligence(AI)and object recognition * Develop a simple object recognition system using CNNs * Integrate AI with ROS to enable your robot to recognize objects Who this book is for Artificial Vision and Language Processing for Robotics is for robotics engineers who want to learn how to integrate computer vision and deep learning techniques to create complete robotic systems. It will prove beneficial to you if you have working knowledge of Python and a background in deep learning. Knowledge of the ROS is a plus.

A comprehensive guide to building full stack applications covering frontend and server-side programming, data management, and web security Key Features * Unleash the power of React Hooks to build interactive and complex user interfaces * Build scalable full stack applications designed to meet demands of modern users * Understand how the Axios library simplifies CRUD operations Book Description React Hooks have changed the way React components are coded. They enable you to write components in a more intuitive way without using classes, which makes your code easier to read and maintain. Building on from the previous edition, this book is updated with React Hooks and the latest changes introduced in create-react-app and Spring Boot 2.1. This book starts with a brief introduction to Spring Boot. You’ll understand how to use dependency injection and work with the data access layer of Spring using Hibernate as the ORM tool. You’ll then learn how to build your own RESTful API endpoints for web applications. As you advance, the book introduces you to other Spring components, such as Spring Security to help you secure the backend. Moving on, you’ll explore React and its app development environment and components for building your frontend. Finally, you’ll create a Docker container for your application by implementing the best practices that underpin professional full stack web development. By the end of this book, you’ll be equipped with all the knowledge you need to build modern full stack applications with Spring Boot for the backend and React for the frontend. What you will learn * Create a RESTful web service with Spring Boot * Grasp the fundamentals of dependency injection and how to use it for backend development * Discover techniques for securing the backend using Spring Security * Understand how to use React for frontend programming * Benefit from the Heroku cloud server by deploying your application to it * Delve into the techniques for creating unit tests using JUnit * Explore the Material UI component library to make more user-friendly user interfaces Who this book is for If you are a Java developer familiar with Spring, but are new to building full stack applications, this is the book for you.

Leverage the power of reward-based training for your deep learning models with Python Key Features * Understand Q-learning algorithms to train neural networks using Markov Decision Process (MDP) * Study practical deep reinforcement learning using Q-Networks * Explore state-based unsupervised learning for machine learning models Book Description Q-learning is a machine learning algorithm used to solve optimization problems in artificial intelligence (AI). It is one of the most popular fields of study among AI researchers. This book starts off by introducing you to reinforcement learning and Q-learning, in addition to helping you get familiar with OpenAI Gym as well as libraries such as Keras and TensorFlow. A few chapters into the book, you will gain insights into modelfree Q-learning and use deep Q-networks and double deep Q-networks to solve complex problems. This book will guide you in exploring use cases such as self-driving vehicles and OpenAI Gym’s CartPole problem. You will also learn how to tune and optimize Q-networks and their hyperparameters. As you progress, you will understand the reinforcement learning approach to solving real-world problems. You will also explore how to use Q-learning and related algorithms in real-world applications such as scientific research. Toward the end, you’ll gain a sense of what’s in store for reinforcement learning. By the end of this book, you will be equipped with the skills you need to solve reinforcement learning problems using Q-learning algorithms with OpenAI Gym, Keras, and TensorFlow. What you will learn * Explore the fundamentals of reinforcement learning and the state-action-reward process * Understand Markov decision processes * Get well versed with libraries such as Keras, and TensorFlow * Create and deploy model-free learning and deep Q-learning agents with TensorFlow, Keras, and OpenAI Gym * Choose and optimize a Q-Network’s learning parameters and fine-tune its performance * Discover real-world applications and use cases of Q-learning Who this book is for If you are a machine learning developer, engineer, or professional who wants to delve into the deep learning approach for a complex environment, then this is the book for you. Proficiency in Python programming and basic understanding of decision-making in reinforcement learning is assumed.

Gain hands-on experience with industry-standard data analysis and machine learning tools in Python Key Features * Learn techniques to use data to identify the exact problem to be solved * Visualize data using different graphs * Identify how to select an appropriate algorithm for data extraction Book Description Data Science Projects with Python is designed to give you practical guidance on industry-standard data analysis and machine learning tools in Python, with the help of realistic data. The book will help you understand how you can use pandas and Matplotlib to critically examine a dataset with summary statistics and graphs, and extract the insights you seek to derive. You will continue to build on your knowledge as you learn how to prepare data and feed it to machine learning algorithms, such as regularized logistic regression and random forest, using the scikit-learn package. You’ll discover how to tune the algorithms to provide the best predictions on new and, unseen data. As you delve into later chapters, you’ll be able to understand the working and output of these algorithms and gain insight into not only the predictive capabilities of the models but also their reasons for making these predictions. By the end of this book, you will have the skills you need to confidently use various machine learning algorithms to perform detailed data analysis and extract meaningful insights from unstructured data. What you will learn * Install the required packages to set up a data science coding environment * Load data into a Jupyter Notebook running Python * Use Matplotlib to create data visualizations * Fit a model using scikit-learn * Use lasso and ridge regression to reduce overfitting * Fit and tune a random forest model and compare performance with logistic regression * Create visuals using the output of the Jupyter Notebook Who this book is for If you are a data analyst, data scientist, or a business analyst who wants to get started with using Python and machine learning techniques to analyze data and predict outcomes, this book is for you. Basic knowledge of computer programming and data analytics is a must. Familiarity with mathematical concepts such as algebra and basic statistics will be useful.

Develop technical skills and expertise to automate AWS networking tasks Key Features * A fast paced guide that will help you pass the exam with confidence * Learn advanced skill sets to build effective AWS networking solutions * Enhance your AWS skills with practice exercises and mock tests Book Description Amazon has recently come up a with specialty certifications which validates a particular user's expertise that he/she would want to build a career in. Since the Cloud market now demands of AWS networking skills this becomes the most wanted certification to upheld ones industry portfolio. This book would be your ideal companion to getting skilled with complex and creative networking solutions. Cloud practitioners or associate-level certified individuals interested in validating advanced skills in networking can opt for this practical guide. This book will include topics that will help you design and implement AWS and hybrid IT network architectures along with some network automation tasks. You will also delve deep into topics that will help you design and maintain network architecture for all AWS services. Like most of our certification guides this book will also follow a unique approach of testing your learning with chapter-level practice exercises and certification-based mock tests. The exam mock tests will help you gauge whether you are ready to take the certification exam or not. This book will also be an advanced guide for networking professionals to enhance their networking skills and get certified. By the end of this book, you will be all equipped with AWS networking concepts and techniques and will have mastered core architectural best practices. What you will learn * Formulate solution plans and provide guidance on AWS architecture best practices * Design and deploy scalable, highly available, and fault-tolerant systems on AWS * Identify the tools required to replicate an on-premises network in AWS * Analyze the access and egress of data to and from AWS * Select the appropriate AWS service based on data, compute, database, or security requirements * Estimate AWS costs and identify cost control mechanisms Who this book is for If you are a system administrator, or a network engineer interested in getting certified with an advanced Cloud networking certification then this book is for you. Prior experience in Cloud administration and networking would be necessary.

Design and create neural networks with deep learning and artificial intelligence principles using OpenAI Gym, TensorFlow, and Keras Key Features * Explore neural network architecture and understand how it functions * Learn algorithms to solve common problems using back propagation and perceptrons * Understand how to apply neural networks to applications with the help of useful illustrations Book Description Neural networks play a very important role in deep learning and artificial intelligence (AI), with applications in a wide variety of domains, right from medical diagnosis, to financial forecasting, and even machine diagnostics. Hands-On Neural Networks is designed to guide you through learning about neural networks in a practical way. The book will get you started by giving you a brief introduction to perceptron networks. You will then gain insights into machine learning and also understand what the future of AI could look like. Next, you will study how embeddings can be used to process textual data and the role of long short-term memory networks (LSTMs) in helping you solve common natural language processing (NLP) problems. The later chapters will demonstrate how you can implement advanced concepts including transfer learning, generative adversarial networks (GANs), autoencoders, and reinforcement learning. Finally, you can look forward to further content on the latest advancements in the field of neural networks. By the end of this book, you will have the skills you need to build, train, and optimize your own neural network model that can be used to provide predictable solutions. What you will learn * Learn how to train a network by using backpropagation * Discover how to load and transform images for use in neural networks * Study how neural networks can be applied to a varied set of applications * Solve common challenges faced in neural network development * Understand the transfer learning concept to solve tasks using Keras and Visual Geometry Group (VGG) network * Get up to speed with advanced and complex deep learning concepts like LSTMs and NLP * Explore innovative algorithms like GANs and deep reinforcement learning Who this book is for If you are interested in artificial intelligence and deep learning and want to further your skills, then this intermediate-level book is for you. Some knowledge of statistics will help you get the most out of this book.

A practical guide to building high performance systems for object detection, segmentation, video processing, smartphone applications, and more. This book is based on the alpha version of TensorFlow 2. Key Features * Discover how to build, train, and serve your own deep neural networks with TensorFlow 2 and Keras * Apply modern solutions to a wide range of applications such as object detection and video analysis * Learn how to run your models on mobile devices and webpages and improve their performance Book Description Computer vision solutions are becoming increasingly common, making their way in fields such as health, automobile, social media, and robotics. This book will help you explore TensorFlow 2, the brand new version of Google's open source framework for machine learning. You will understand how to benefit from using convolutional neural networks (CNNs) for visual tasks. Hands-On Computer Vision with TensorFlow 2 starts with the fundamentals of computer vision and deep learning, teaching you how to build a neural network from scratch. You will discover the features that have made TensorFlow the most widely used AI library, along with its intuitive Keras interface, and move on to building, training, and deploying CNNs efficiently. Complete with concrete code examples, the book demonstrates how to classify images with modern solutions, such as Inception and ResNet, and extract specific content using You Only Look Once (YOLO), Mask R-CNN, and U-Net. You will also build Generative Adversarial Networks (GANs) and Variational Auto-Encoders (VAEs) to create and edit images, and LSTMs to analyze videos. In the process, you will acquire advanced insights into transfer learning, data augmentation, domain adaptation, and mobile and web deployment, among other key concepts. By the end of the book, you will have both the theoretical understanding and practical skills to solve advanced computer vision problems with TensorFlow 2.0. What you will learn * Create your own neural networks from scratch * Classify images with modern architectures including Inception and ResNet * Detect and segment objects in images with YOLO, Mask R-CNN, and U-Net * Tackle problems in developing self-driving cars and facial emotion recognition systems * Boost your application’s performance with transfer learning, GANs, and domain adaptation * Use recurrent neural networks for video analysis * Optimize and deploy your networks on mobile devices and in the browser Who this book is for If you’re new to deep learning and have some background in Python programming and image processing, like reading/writing image files and editing pixels, this book is for you. Even if you’re an expert curious about the new TensorFlow 2 features, you’ll find this book useful. While some theoretical explanations require knowledge in algebra and calculus, the book covers concrete examples for learners focused on practical applications such as visual recognition for self-driving cars and smartphone apps.

Explore the entire Hyperledger blockchain family, including frameworks such as Fabric, Sawtooth, Indy, Burrow, and Iroha; and tools such as Composer, Explorer, and Caliper. Key Features * Plan, design, and create a full-fledged private decentralized application using Hyperledger services * Master the ins and outs of the Hyperledger network using real-world examples * Packed with problem-solution-based recipes to tackle pain areas in the blockchain development cycle Book Description Hyperledger is an open-source project and creates private blockchain applications for a range of domains. This book will be your desk reference as you explore common and not-so-common challenges faced while building blockchain networks using Hyperledger services. We'll work through all Hyperledger platform modules to understand their services and features and build end-to-end blockchain applications using various frameworks and tools supported by Hyperledger. This book's independent, recipe-based approach (packed with real-world examples) will familiarize you with the blockchain development cycle. From modeling a business network to integrating with various tools, you will cover it all. We'll cover common and not-so-common challenges faced in the blockchain life cycle. Later, we'll delve into how we can interact with the Hyperledger Fabric blockchain, covering all the principles you need to master, such as chaincode, smart contracts, and much more. We'll also address the scalability and security issues currently faced in blockchain development. By the end of this book, you will be able to implement each recipe to plan, design, and create a full-fledged, private, decentralized application to meet organizational needs. What you will learn * Create the most popular permissioned blockchain network with Fabric and Composer * Build permissioned and permission-less blockchains using Sawtooth * Utilize built-in Iroha asset/account management with role-based permissions * Implement and run Ethereum smart contracts with Burrow * Get to grips with security and scalability in Hyperledger * Explore and view blockchain data using Hyperledger Explorer * Produce reports containing performance indicators and benchmarks using Caliper Who this book is for This book is for blockchain developers who want to understand how they can apply Hyperledger services in their day-to-day projects. This book uses a recipe-based approach to help you use Hyperledger to build powerful, decentralized autonomous applications. We assume the reader has a basic knowledge of the Blockchain technology and cryptography concepts

Learn and explore the fundamentals of data analysis with power of Mathematica About This Book Use the power of Mathematica to analyze data in your applications Discover the capabilities of data classification and pattern recognition offered by Mathematica Use hundreds of algorithms for time series analysis to predict the future Who This Book Is For The book is for those who want to learn to use the power of Mathematica to analyze and process data. Perhaps you are already familiar with data analysis but have never used Mathematica, or you know Mathematica but you are new to data analysis. With the help of this book, you will be able to quickly catch up on the key points for a successful start. What You Will Learn Import data from different sources to Mathematica Link external libraries with programs written in Mathematica Classify data and partition them into clusters Recognize faces, objects, text, and barcodes Use Mathematica functions for time series analysis Use algorithms for statistical data processing Predict the result based on the observations In Detail There are many algorithms for data analysis and it’s not always possible to quickly choose the best one for each case. Implementation of the algorithms takes a lot of time. With the help of Mathematica, you can quickly get a result from the use of a particular method, because this system contains almost all the known algorithms for data analysis. If you are not a programmer but you need to analyze data, this book will show you the capabilities of Mathematica when just few strings of intelligible code help to solve huge tasks from statistical issues to pattern recognition. If you're a programmer, with the help of this book, you will learn how to use the library of algorithms implemented in Mathematica in your programs, as well as how to write algorithm testing procedure. With each chapter, you'll be more immersed in the special world of Mathematica. Along with intuitive queries for data processing, we will highlight the nuances and features of this system, allowing you to build effective analysis systems. With the help of this book, you will learn how to optimize the computations by combining your libraries with the Mathematica kernel. Style and approach This book takes a step-by-step approach, accompanied by examples, so you get a better understanding of the logic of writing algorithms for data analysis in Mathematica. We provide a detailed explanation of all the nuances of the Mathematica language, no matter what your level of experience is.

Make applications cross-communicate using Apache Thrift! About This Book Leverage Apache Thrift to enable applications written in different programming languages (Java, C++, Python, PHP, Ruby, and so on) to cross-communicate. Learn to make your services ready for real-world applications by using stepwise examples and modifying code from Industry giants. Be a crackerjack at solving Apache Thrift-related issues. Who This Book Is For If you have some experience of developing applications in one or more languages supported by Apache Thrift (C++, Java, PHP, Python, Ruby, and others) and want to broaden your knowledge and skills in building cross-platform, scalable applications, then this book is for you. What You Will Learn Understand the need for cross-language services and the basics of Apache Thrift. Learn how Apache Thrift works and what problems it solves. Determine when to use Apache Thrift instead of other methods (REST API), and when not to use it. Create and run an example application using Apache Thrift. Use Apache Thrift in your applications written in different languages supported by Apache Thrift (PHP, Python, Ruby, Java, and C++). Handle exceptions and deal with errors. Modify code in different languages.< Use Apache Thrift in the production environments of big applications. In Detail With modern software systems being increasingly complex, providing a scalable communication architecture for applications in different languages is tedious. The Apache Thrift framework is the solution to this problem! It helps build efficient and easy-to-maintain services and offers a plethora of options matching your application type by supporting several popular programming languages, including C++, Java, Python, PHP, Ruby, Erlang, Perl, Haskell, C#, Cocoa, JavaScript, Node.js, Smalltalk, OCaml, and Delphi. This book will help you set aside the basics of service-oriented systems through your first Apache Thrift-powered app. Then, progressing to more complex examples, it will provide you with tips for running large-scale applications in production environments. You will learn how to assess when Apache Thrift is the best tool to be used. To start with, you will run a simple example application, learning the framework's structure along the way; you will quickly advance to more complex systems that will help you solve various real-life problems. Moreover, you will be able to add a communication layer to every application written in one of the popular programming languages, with support for various data types and error handling. Further, you will learn how pre-eminent companies use Apache Thrift in their popular applications. This book is a great starting point if you want to use one of the best tools available to develop cross-language applications in service-oriented architectures. Style and approach A stepwise guide to learning Apache Thrift, with ready-to-run examples explained comprehensively. Advanced topics supply the inspiration for further work.

Unleash the power of Apache Oozie to create and manage your big data and machine learning pipelines in one go About This Book Teaches you everything you need to know to get started with Apache Oozie from scratch and manage your data pipelines effortlessly Learn to write data ingestion workflows with the help of real-life examples from the author’s own personal experience Embed Spark jobs to run your machine learning models on top of Hadoop Who This Book Is For If you are an expert Hadoop user who wants to use Apache Oozie to handle workflows efficiently, this book is for you. This book will be handy to anyone who is familiar with the basics of Hadoop and wants to automate data and machine learning pipelines. What You Will Learn Install and configure Oozie from source code on your Hadoop cluster Dive into the world of Oozie with Java MapReduce jobs Schedule Hive ETL and data ingestion jobs >Import data from a database through Sqoop jobs in HDFS Create and process data pipelines with Pig, hive *s as per business requirements. Run machine learning Spark jobs on Hadoop Create quick Oozie jobs using Hue Make the most of Oozie’s security capabilities by configuring Oozie’s security In Detail As more and more organizations are discovering the use of big data analytics, interest in platforms that provide storage, computation, and analytic capabilities is booming exponentially. This calls for data management. Hadoop caters to this need. Oozie fulfils this necessity for a scheduler for a Hadoop job by acting as a cron to better analyze data. Apache Oozie Essentials starts off with the basics right from installing and configuring Oozie from source code on your Hadoop cluster to managing your complex clusters. You will learn how to create data ingestion and machine learning workflows. This book is sprinkled with the examples and exercises to help you take your big data learning to the next level. You will discover how to write workflows to run your MapReduce, Pig ,Hive, and Sqoop *s and schedule them to run at a specific time or for a specific business requirement using a coordinator. This book has engaging real-life exercises and examples to get you in the thick of things. Lastly, you’ll get a grip of how to embed Spark jobs, which can be used to run your machine learning models on Hadoop. By the end of the book, you will have a good knowledge of Apache Oozie. You will be capable of using Oozie to handle large Hadoop workflows and even improve the availability of your Hadoop environment. Style and approach This book is a hands-on guide that explains Oozie using real-world examples. Each chapter is blended beautifully with fundamental concepts sprinkled in-between case study solution algorithms and topped off with self-learning exercises.

Build your own cloud based Database as a Service using OpenStack Trove About This Book Familiarize yourself with the concept of Database as a Service and make your existing system scalable and efficient with OpenStack Trove Minimize the administrative tasks and complexities of managing your cloud infrastructure This is a fast-paced guide to datastore management on the OpenStack platform using OpenStack Trove Who This Book Is For If you are a DBA / system administrator / architect, or a student who wants to build a Database as a Service based on OpenStack, this book is for you. You should have a basic knowledge of OpenStack components, RDBMS/NoSQL, IaaS, and cloud computing. What You Will Learn Get to grips with the basics of OpenStack and the prerequisites to install Trove Understand the expectations of DBaaS and how Trove can help you achieve them Set up a basic installation of DevStack (Development Stack) in a virtual box Install Trove and utilize its configuration groups to manage and tune databases Use Image builder to create guest images for Trove Utilize Trove to provision your first database instance Back up and restore your databases with the help of Trove In Detail OpenStack has become an extremely popular solution to build public and private clouds with. Database as a Service (DBaaS) enables the delivery of more agile database services at lower costs. Some other benefits of DBaaS are secure database deployments and compliance to standards and best practices. Trove is a DBaaS built on OpenStack and is becoming more popular by the day. Since Trove is one of the most recent projects of OpenStack, DBAs and system administrators can find it difficult to set up and run a DBaaS using OpenStack Trove. This book helps DBAs make that step. We start by introducing you to the concepts of DBaaS and how is it implemented using OpenStack Trove. Following this, we look at implementing OpenStack and deploying Trove. Moving on, you will learn to create guest images to be used with Trove. We then look at how to provision databases in self-service mode, and how to perform administration tasks such as backup and recovery, and fine-tuning databases. At the end of the book, we will examine some advanced features of Trove such as replication. Style and approach This fast-paced, step-by-step guide introduces you to DBaaS, OpenStack Trove, and its components, leading you through building your own Cloud-based DBaaS. Using the DevStack deployment method, you will spend less time on installing OpenStack so you can devote more time to learning how to provision and manage databases in a DBaaS environment.

Unleash the full potential of the Flask web framework by creating simple yet powerful web applications About This Book The most up-to-date book on Flask on the market Create your own world-class applications and master the art of Flask by unravelling its enigma through this journey This step-by-step tutorial is packed with examples on blending different technologies with Flask to get you up and running Who This Book Is For Have you looked at PHP and hated the clunky bloated syntaxOr looked at .Net and wished it was more open and flexibleMaybe you’ve tried your hand at GUI libraries in Python and found them hard to useIf your answer to any one of these questions is a yes, then this is just the book for you. It is also intended for people who know the basics of Python and want to learn how to use it to build powerful solutions with a web front-end. What You Will Learn Build three web applications from the ground up using the powerful Python micro framework, Flask. Dynamically display data to your viewers, based on their requests Store user and static data in SQL and NoSQL databases and use this data to power your web applications Create a good user experience by combining HTML, CSS, and JavaScript Harness the convenience of freely available APIs, including OpenWeatherMap, Open Exchange Rates, and bitly Extend your applications to build advanced functionality, such as a user account control system using Flask-Login Learn about web application security and defend against common attacks, such as SQL injection and XSS In Detail This book will take you on a journey from learning about web development using Flask to building fully functional web applications. In the first major project, we develop a dynamic Headlines application that displays the latest news headlines along with up-to-date currency and weather information. In project two, we build a Crime Map application that is backed by a MySQL database, allowing users to submit information on and the location of crimes in order to plot danger zones and other crime trends within an area. In the final project, we combine Flask with more modern technologies, such as Twitter's Bootstrap and the NoSQL database MongoDB, to create a Waiter Caller application that allows restaurant patrons to easily call a waiter to their table. This pragmatic tutorial will keep you engaged as you learn the crux of Flask by working on challenging real-world applications. Style and approach This book will provide you with rich, practical experience of Flask. Every technology, that is employed along with Flask is comprehensively introduced, while the book focusses on developing web applications. Pointers to educational material are always given if you want to gain in-depth knowledge of the various technologies used.

Discover how to build iOS and watchOS applications in Swift 2 using XcodeAbout This BookGets you up and running with Swift programming without any prior iOS development experience.A fast paced guide showing best practices and lets you get up to speed with Swift to quickly build your own iOS applicationsA unique practical approach to make your life with Swift easy.Who This Book Is ForAre you interested in learning SwiftDo you want to write iOS applications in SwiftIf yes, then this is the book for you. No prior iOS programming experience is assumed; however, having some experience with any programming language will be beneficial.What You Will LearnDive into Swift and explore its innovative and powerful syntaxWork with Swift in Xcode to get a unique and productive approach to developmentFind out how to create complete iOS applicationsDiscover rapid prototyping with a Swift playgroundGet to know how to use the Swift storyboard to develop multi-page applicationsGet to grips with parsing JSON and XML data from network sourcesBuild a network client for GitHub repositories, with full source code on GitHubIn DetailSwift was considered one of the biggest innovations last year, and certainly with Swift 2 announced at WWDC in 2015, this segment of the developer space will continue to be hot and dominating.This is a fast-paced guide to provide an overview of Swift programming and then walks you through in detail how to write iOS applications. Progress through chapters on custom views, networking, parsing and build a complete application as a Git repository, all by using Swift as the core languageStyle and approachThis fast-paced practical guide will quickly give you hands-on experience with all the features of Swift programming. Following the practical examples in the book will help you successfully create your own iOS applications.

Learn the fundamentals of Cython to extend the legacy of your applicationsAbout This BookLearn how to extend C applications with pure Python codeGet more from Python – you’ll not only learn Cython, you’ll also unlock a greater understanding of how to harness PythonPacked with tips and tricks that make Cython look easy, dive into this accessible programming guide and find out what happens when you bring C and Python together!Who This Book Is ForThis book is for developers who are familiar with the basics of C and Python programming and wish to learn Cython programming to extend their applications.What You Will LearnReuse Python logging in CMake an IRC bot out of your C applicationExtend an application so you have a web server for rest callsPractice Cython against your C++ codeDiscover tricks to work with Python ConfigParser in CCreate Python bindings for native librariesFind out about threading and concurrency related to GILExpand Terminal Multiplexer Tmux with CythonIn DetailCython is a hybrid programming language used to write C extensions for Python language. Combining the practicality of Python and speed and ease of the C language it’s an exciting language worth learning if you want to build fast applications with ease.This new edition of Learning Cython Programming shows you how to get started, taking you through the fundamentals so you can begin to experience its unique powers.You’ll find out how to get set up, before exploring the relationship between Python and Cython. You’ll also look at debugging Cython, before moving on to C++ constructs, Caveat on C++ usage, Python threading and GIL in Cython. Finally, you’ll learn object initialization and compile time, and gain a deeper insight into Python 3, which will help you not only become a confident Cython developer, but a much more fluent Python developer too.Style and approachThis practical and a fast-paced guide gives you all the information you need to start programming using Cython.

Transform physical phenomena into computer-acceptable data using a truly object-oriented language About This Book Create your own data acquisition system independently using LabVIEW and build interactive dashboards Collect data using National Instrument's and third-party, open source, affordable hardware Step-by-step real-world examples using various tools that illustrate the fundamentals of data acquisition Who This Book Is For If you are an engineer, scientist, experienced hobbyist, or student, you will highly benefit from the content and examples illustrated in this book. A working knowledge of precision testing, measurement instruments, and electronics, as well as a background in computer fundamentals and programming is expected. What You Will Learn Create a virtual instrument which highlights common functionality of LabVIEW Get familiarized with common buses such as Serial, GPIB, and SCPI commands Staircase signal acquisition using NI-DAQmx Discover how to measure light intensity and distance Master LabVIEW debugging techniques Build a data acquisition application complete with an installer and required drivers Utilize open source microcontroller Arduino and a 32-bit Arduino compatible Uno32 using LabVIEW programming environment In Detail NI LabVIEW's intuitive graphical interface eliminates the steep learning curve associated with text-based languages such as C or C++. LabVIEW is a proven and powerful integrated development environment to interact with measurement and control hardware, analyze data, publish results, and distribute systems. This hands-on tutorial guide helps you harness the power of LabVIEW for data acquisition. This book begins with a quick introduction to LabVIEW, running through the fundamentals of communication and data collection. Then get to grips with the auto-code generation feature of LabVIEW using its GUI interface. You will learn how to use NI-DAQmax Data acquisition VIs, showing how LabVIEW can be used to appropriate a true physical phenomenon (such as temperature, light, and so on) and convert it to an appropriate data type that can be manipulated and analyzed with a computer. You will also learn how to create Distribution Kit for LabVIEW, acquainting yourself with various debugging techniques offered by LabVIEW to help you in situations where bugs are not letting you run your programs as intended. By the end of the book, you will have a clear idea how to build your own data acquisition system independently and much more. Style and approach A hands-on practical guide that starts by laying down the software and hardware foundations necessary for subsequent data acquisition-intensive chapters. The book is packed full of specific examples with software screenshots and schematic diagrams to guide you through the creation of each virtual instrument.

This book is your guide to exploring the possibilities in the field of deep learning, making use of Google's TensorFlow. You will learn about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data. About This Book ? Explore various possibilities with deep learning and gain amazing insights from data using Google’s brainchild-- TensorFlow ? Want to learn what more can be done with deep learning? Explore various neural networks with the help of this comprehensive guide ? Rich in concepts, advanced guide on deep learning that will give you background to innovate in your environment Who This Book Is For If you are a data scientist who performs machine learning on a regular basis, are familiar with deep neural networks, and now want to gain expertise in working with convoluted neural networks, then this book is for you. Some familiarity with C++ or Python is assumed. What You Will Learn ? Set up your computing environment and install TensorFlow ? Build simple TensorFlow graphs for everyday computations ? Apply logistic regression for classification with TensorFlow ? Design and train a multilayer neural network with TensorFlow ? Intuitively understand convolutional neural networks for image recognition ? Bootstrap a neural network from simple to more accurate models ? See how to use TensorFlow with other types of networks ? Program networks with SciKit-Flow, a high-level interface to TensorFlow In Detail Dan Van Boxel’s Deep Learning with TensorFlow is based on Dan’s best-selling TensorFlow video course. With deep learning going mainstream, making sense of data and getting accurate results using deep networks is possible. Dan Van Boxel will be your guide to exploring the possibilities with deep learning; he will enable you to understand data like never before. With the efficiency and simplicity of TensorFlow, you will be able to process your data and gain insights that will change how you look at data. With Dan’s guidance, you will dig deeper into the hidden layers of abstraction using raw data. Dan then shows you various complex algorithms for deep learning and various examples that use these deep neural networks. You will also learn how to train your machine to craft new features to make sense of deeper layers of data. In this book, Dan shares his knowledge across topics such as logistic regression, convolutional neural networks, recurrent neural networks, training deep networks, and high level interfaces. With the help of novel practical examples, you will become an ace at advanced multilayer networks, image recognition, and beyond. Style and Approach This book is your go-to guide to becoming a deep learning expert in your organization. Dan helps you evaluate common and not-so-common deep neural networks with the help of insightful examples that you can relate to, and show how they can be exploited in the real world with complex raw data.

A practical guide to help you undertand the ability of Apache jMeter to load and performance test various server types in a more efficient way. About This Book ? Use jMeter to create and run tests to improve the performance of your webpages and applications ? Learn to build a test plan for your websites and analyze the results ? Unleash the power of various features and changes introduced in Apache jMeter 3.0 Who This Book Is For This book is for software professionals who want to understand and improve the performance of their applications with Apache jMeter. What You Will Learn ? See why performance testing is necessary and learn how to set up JMeter ? Record and test with JMeter ? Handle various form inputs in JMeter and parse results during testing ? Manage user sessions in web applications in the context of a JMeter test ? Monitor JMeter results in real time ? Perform distributed testing with JMeter ? Get acquainted with helpful tips and best practices for working with JMeter In Detail JMeter is a Java application designed to load and test performance for web application. JMeter extends to improve the functioning of various other static and dynamic resources. This book is a great starting point to learn about JMeter. It covers the new features introduced with JMeter 3 and enables you to dive deep into the new techniques needed for measuring your website performance. The book starts with the basics of performance testing and guides you through recording your first test scenario, before diving deeper into JMeter. You will also learn how to configure JMeter and browsers to help record test plans. Moving on, you will learn how to capture form submission in JMeter, dive into managing sessions with JMeter and see how to leverage some of the components provided by JMeter to handle web application HTTP sessions. You will also learn how JMeter can help monitor tests in real-time. Further, you will go in depth into distributed testing and see how to leverage the capabilities of JMeter to accomplish this. You will get acquainted with some tips and best practices with regard to performance testing. By the end of the book, you will have learned how to take full advantage of the real power behind Apache JMeter. Style and approach The book is a practical guide starting with introducing the readers to the importance of automated testing. It will then be a beginner’s journey from getting introduced to Apache jMeter to an in-detail discussion of more advanced features and possibilities with it.

Learn the techniques used by the most successful IT people in the world. About This Book ? Get real-life case studies for different IT roles, developers, testers, analysts, project managers, DBAs ? Identify with your IT scenarios and take the right decision to move up in your career ? Improve your EQ and face any difficult scenario confidently and effectively Who This Book Is For This book is for professionals across the IT domain who work as developers, administrators, architects, administrators system analysts, and so on, who want to create a better working environment around them by improving their own emotional intelligence. This book assumes that you are a beginner to emotional intelligence and will help you understand the basic concepts before helping you with real life scenarios. What You Will Learn ? Improve your observation skills to understand people better ? Know how to identify what motivates you and those around you ? Develop strategies for working more effectively with others ? Increase your capacity to influence people and improve your communication skills ? Understand how to successfully complete tasks through other people ? Discover how to control the emotional content of your decision-making In Detail This book will help you discover your emotional quotient (EQ) through practices and techniques that are used by the most successful IT people in the world. It will make you familiar with the core skills of Emotional Intelligence, such as understanding the role that emotions play in life, especially in the workplace. You will learn to identify the factors that make your behavior consistent, not just to other employees, but to yourself. This includes recognizing, harnessing, predicting, fostering, valuing, soothing, increasing, decreasing, managing, shifting, influencing or turning around emotions and integrating accurate emotional information into decision-making, reasoning, problem solving, etc., because, emotions run business in a way that spreadsheets and logic cannot. When a deadline lurks, you’ll know the steps you need to take to keep calm and composed. You’ll find out how to meet the deadline, and not get bogged down by stress. We’ll explain these factors and techniques through real-life examples faced by IT employees and you’ll learn using the choices that they made. This book will give you a detailed analysis of the events and behavioral pattern of the employees during that time. This will help you improve your own EQ to the extent that you don’t just survive, but thrive in a competitive IT industry. Style and approach You will be taken through real-life events faced by IT employees in different scenarios. These real-world cases are analyzed along with the response of the employees, which will help you to develop your own emotion intelligence quotient and face any difficult scenario confidently and effectively.

Over 50 recipes on the core features of Apache Mesos and running big data frameworks in Mesos About This Book ? Learn to install and configure Mesos to suit the needs of your organization ? Follow step-by-step instructions to deploy application frameworks on top of Mesos, saving you many hours of research and trial and error ? Use this practical guide packed with powerful recipes to implement Mesos and easily integrate it with other application frameworks Who This Book Is For This book is for system administrators, engineers, and big data programmers. Basic experience with big data technologies such as Hadoop or Spark would be useful but is not essential. A working knowledge of Apache Mesos is expected. What You Will Learn ? Set up Mesos on different operating systems ? Use the Marathon and Chronos frameworks to manage multiple applications ? Work with Mesos and Docker ? Integrate Mesos with Spark and other big data frameworks ? Use networking features in Mesos for effective communication between containers ? Configure Mesos for high availability using Zookeeper ? Secure your Mesos clusters with SASL and Authorization ACLs ? Solve everyday problems and discover the best practices In Detail Apache Mesos is open source cluster sharing and management software. Deploying and managing scalable applications in large-scale clustered environments can be difficult, but Apache Mesos makes it easier with efficient resource isolation and sharing across application frameworks. The goal of this book is to guide you through the practical implementation of the Mesos core along with a number of Mesos supported frameworks. You will begin by installing Mesos and then learn how to configure clusters and maintain them. You will also see how to deploy a cluster in a production environment with high availability using Zookeeper. Next, you will get to grips with using Mesos, Marathon, and Docker to build and deploy a PaaS. You will see how to schedule jobs with Chronos. We’ll demonstrate how to integrate Mesos with big data frameworks such as Spark, Hadoop, and Storm. Practical solutions backed with clear examples will also show you how to deploy elastic big data jobs. You will find out how to deploy a scalable continuous integration and delivery system on Mesos with Jenkins. Finally, you will configure and deploy a highly scalable distributed search engine with ElasticSearch. Throughout the course of this book, you will get to know tips and tricks along with best practices to follow when working with Mesos. Style and approach This step-by-step guide is packed with powerful recipes on using Apache Mesos and shows its integration with containers and big data frameworks.

Discover how to build full stack web applications with the Raspberry Pi 3 About This Book ? Leverage JavaScript, HTML5, and Cloud APIs to create visual representations and interactive web pages. ? Learn to install and use a Node.js-based web framework to develop Raspberry Pi 3-powered web applications. ? A step-by-step guide that will cover from setting up a embedded system to developing embedded, device-powered interactive web applications. Who This Book Is For This book is aimed at hobbyist, enthusiasts, and developers eager to develop embedded device-powered web applications. Prior programming experience with JavaScript, HTML5, and Node.JS will be beneficial. What You Will Learn ? Get up and running with your Raspberry Pi ? Go full stack! Learn about the end-to-end development process for web applications, right from the OS up to the actual HTML web interface ? Discover that JavaScript is one of the fastest growing languages today, and is the only language that can be used both on a browser and server. This book will empower you to develop in a complete JavaScript stack ? See that the IoT is everywhere!Connect your application to the outside world. Make use of sensors in your Raspberry Pi to give your application an edge, and unleash the full power of the Internet of Things ? Build a rich UI with beautiful charts and data visualizations that can run on any browser ? Make your software data-driven. Learn how to utilize SQLite to collect and analyze data from multiple systems In Detail Modern web technology and portable computing together have enabled huge advances in the Internet of Things (IoT) space,as well as in areas such as machine learning and big data. The Raspberry Pi is a very popular portable computer for running full stack web applications. This book will empower you to master this rapidly evolving technology to develop complex web applications and interfaces. This book starts by familiarizing you with the various components that make up the web development stack and that will integrate into your Raspberry Pi-powered web applications. It also introduces the Raspberry Pi computer and teach you how to get up and running with a brand new one. Next, this book introduces you to the different kinds of sensor you’ll use to make your applications; using these skills, you will be able to create full stack web applications and make them available to users via a web interface. Later, this book will also teach you how to build interactive web applications using JavaScript and HTML5 for the visual representation of sensor data. Finally, this book will teach you how to use a SQLite database to store and retrieve sensor data from multiple Raspberry Pi computers. By the end of this book you will be able to create complex full stack web applications on the Raspberry Pi 3 and will have improved your application’s performance and usability. Style and approach Step-by-step instructions on developing a full stack web application and deploying it to the Cloud.