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 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.

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.

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.

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.

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.

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

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.

Untangle the complexity of OpenStack clouds through this practical tutorial About This Book Navigate through the complex jungle of components in OpenStack using practical instructions This book helps administrators, cloud engineers, and even developers to consolidate and control pools of compute, networking, and storage resources Learn to use the centralized dashboard and administration panel to monitor large-scale deployments Who This Book Is For This book is perfect for administrators, cloud engineers, and operators who want to get started with OpenStack, solve basic problems encountered during deployment, and get up to speed with the latest release of OpenStack. Familiarity with the Linux command line and experience with Linux system administration is expected. What You Will Learn Brush up on the latest release, and how it affects the various components Install OpenStack using the Packstack and RDO Manager installation tool Learn to convert a computer node that supports Docker containers Implement Ceph Block Device images with OpenStack Create and allocate virtual networks, routers and IP addresses to OpenStack Tenants. Configuring and Launching a Docker container. In Detail OpenStack is a widely popular platform for cloud computing. Applications that are built for this platform are resilient to failure and convenient to scale. This book, an update to our extremely popular OpenStack Essentials (published in May 2015) will help you master not only the essential bits, but will also examine the new features of the latest OpenStack release - Mitaka; showcasing how to put them to work straight away. This book begins with the installation and demonstration of the architecture. This book will tech you the core 8 topics of OpenStack. They are Keystone for Identity Management, Glance for Image management, Neutron for network management, Nova for instance management, Cinder for Block storage, Swift for Object storage, Ceilometer for Telemetry and Heat for Orchestration. Further more you will learn about launching and configuring Docker containers and also about scaling them horizontally. You will also learn about monitoring and Troubleshooting OpenStack. Style and approach This book offers step-by-step practical instructions to help you quickly navigate through the complexities of OpenStack

Achieve scalability and high availability without compromising on performance About This Book See how to get 100 percent uptime with your Cassandra applications using this easy-follow guide Learn how to avoid common and not-so-common mistakes while working with Cassandra using this highly practical guide Get familiar with the intricacies of working with Cassandra for high availability in your work environment with this go-to-guide Who This Book Is For If you are a developer or DevOps engineer who has basic familiarity with Cassandra and you want to become an expert at creating highly available, fault tolerant systems using Cassandra, this book is for you. What You Will Learn Understand how the core architecture of Cassandra enables highly available applications Use replication and tunable consistency levels to balance consistency, availability, and performance Set up multiple data centers to enable failover, load balancing, and geographic distribution Add capacity to your cluster with zero downtime Take advantage of high availability features in the native driver Create data models that scale well and maximize availability Understand common anti-patterns so you can avoid them Keep your system working well even during failure scenarios In Detail Apache Cassandra is a massively scalable, peer-to-peer database designed for 100 percent uptime, with deployments in the tens of thousands of nodes, all supporting petabytes of data. This book offers a practical insight into building highly available, real-world applications using Apache Cassandra. The book starts with the fundamentals, helping you to understand how Apache Cassandra’s architecture allows it to achieve 100 percent uptime when other systems struggle to do so. You’ll get an excellent understanding of data distribution, replication, and Cassandra’s highly tunable consistency model. Then we take an in-depth look at Cassandra's robust support for multiple data centers, and you’ll see how to scale out a cluster. Next, the book explores the domain of application design, with chapters discussing the native driver and data modeling. Lastly, you’ll find out how to steer clear of common anti-patterns and take advantage of Cassandra’s ability to fail gracefully. Style and approach This practical guide will get you implementing Cassandra right from the design to creating highly available systems. Through a systematic, step-by-step approach, you will learn different aspects of building highly available Cassandra applications and all this with the help of easy-to-follow examples, tips, and tricks.

A practical guide designed to get you from basics to current state of art in computer vision systems. About This Book ? Master the different tasks associated with Computer Vision and develop your own Computer Vision applications with ease ? Leverage the power of Python, Tensorflow, Keras, and OpenCV to perform image processing, object detection, feature detection and more ? With real-world datasets and fully functional code, this book is your one-stop guide to understanding Computer Vision Who This Book Is For This book is for machine learning practitioners and deep learning enthusiasts who want to understand and implement various tasks associated with Computer Vision and image processing in the most practical manner possible. Some programming experience would be beneficial while knowing Python would be an added bonus. What You Will Learn ? Learn the basics of image manipulation with OpenCV ? Implement and visualize image filters such as smoothing, dilation, histogram equalization, and more ? Set up various libraries and platforms, such as OpenCV, Keras, and Tensorflow, in order to start using computer vision, along with appropriate datasets for each chapter, such as MSCOCO, MOT, and Fashion-MNIST ? Understand image transformation and downsampling with practical implementations. ? Explore neural networks for computer vision and convolutional neural networks using Keras ? Understand working on deep-learning-based object detection such as Faster-R-CNN, SSD, and more ? Explore deep-learning-based object tracking in action ? Understand Visual SLAM techniques such as ORB-SLAM In Detail In this book, you will find several recently proposed methods in various domains of computer vision. You will start by setting up the proper Python environment to work on practical applications. This includes setting up libraries such as OpenCV, TensorFlow, and Keras using Anaconda. Using these libraries, you'll start to understand the concepts of image transformation and filtering. You will find a detailed explanation of feature detectors such as FAST and ORB; you'll use them to find similar-looking objects. With an introduction to convolutional neural nets, you will learn how to build a deep neural net using Keras and how to use it to classify the Fashion-MNIST dataset. With regard to object detection, you will learn the implementation of a simple face detector as well as the workings of complex deep-learning-based object detectors such as Faster R-CNN and SSD using TensorFlow. You'll get started with semantic segmentation using FCN models and track objects with Deep SORT. Not only this, you will also use Visual SLAM techniques such as ORB-SLAM on a standard dataset. By the end of this book, you will have a firm understanding of the different computer vision techniques and how to apply them in your applications. Style and approach Step-by-step guide filled with real-world, practical examples for understanding and applying various Computer Vision techniques

5 real-world projects to help you master deep learning concepts About This Book ? Master the different deep learning paradigms and build real-world projects related to text generation, sentiment analysis, fraud detection, and more ? Get to grips with R's impressive range of Deep Learning libraries and frameworks such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec ? Practical projects that show you how to implement different neural networks with helpful tips, tricks, and best practices Who This Book Is For Machine learning professionals and data scientists looking to master deep learning by implementing practical projects in R will find this book a useful resource. A knowledge of R programming and the basic concepts of deep learning is required to get the best out of this book. What You Will Learn ? Instrument Deep Learning models with packages such as deepnet, MXNetR, Tensorflow, H2O, Keras, and text2vec ? Apply neural networks to perform handwritten digit recognition using MXNet ? Get the knack of CNN models, Neural Network API, Keras, and TensorFlow for traffic sign classification ? Implement credit card fraud detection with Autoencoders ? Master reconstructing images using variational autoencoders ? Wade through sentiment analysis from movie reviews ? Run from past to future and vice versa with bidirectional Long Short-Term Memory (LSTM) networks ? Understand the applications of Autoencoder Neural Networks in clustering and dimensionality reduction In Detail R is a popular programming language used by statisticians and mathematicians for statistical analysis, and is popularly used for deep learning. Deep Learning, as we all know, is one of the trending topics today, and is finding practical applications in a lot of domains. This book demonstrates end-to-end implementations of five real-world projects on popular topics in deep learning such as handwritten digit recognition, traffic light detection, fraud detection, text generation, and sentiment analysis. You'll learn how to train effective neural networks in R—including convolutional neural networks, recurrent neural networks, and LSTMs—and apply them in practical scenarios. The book also highlights how neural networks can be trained using GPU capabilities. You will use popular R libraries and packages—such as MXNetR, H2O, deepnet, and more—to implement the projects. By the end of this book, you will have a better understanding of deep learning concepts and techniques and how to use them in a practical setting. Style and approach This book's unique, learn-as-you-do approach ensures the reader builds on his understanding of deep learning progressively with each project. This book is designed in such a way that implementing each project will empower you with a unique skillset and enable you to implement the next project more confidently.

Become an Ethereum Blockchain developer using a blend of concepts and hands-on implementations About This Book ? Understand the Ethereum Ecosystem and its differences from its rich cousin Bitcoin ? Explore the Solidity programming language and smart contract optimizations ? Get a developer’s perspective of Blockchain-as-a-technology with exposure to common challenges faced while building decentralized applications Who This Book Is For If you want to know the ins and outs of the Ethereum network and build your own decentralized applications, then this book is what you need! This book is for anyone who is interested in blockchain and wants to become an Ethereum developer. It’s ideal for existing Ethereum developers who want to develop Ethereum using smart contracts. Basic knowledge of cryptography is expected but is not mandatory. What You Will Learn ? Know how to build your own smart contracts and cryptocurrencies ? Understand the Solidity language ? Find out about data types, control structure, functions, inheritance, mathematical operations, and much more ? See the various types of forks and discover how they are related to Ethereum ? Get to know the various concepts of web3.js and its APIs so you can build client-side apps ? Build a DAO from scratch and acquire basic knowledge of DApps on Ethercast ? Be guided through the project so you can optimize EVM for smart contracts ? Build your own decentralized applications (DApps) by taking a practical approach In Detail Ethereum is a public, blockchain-based distributed computing platform featuring smart contract functionality. This book is your one-stop guide to blockchain and Ethereum smart contract development. We start by introducing you to the basics of blockchain. You'll learn about hash functions, Merkle trees, forking, mining, and much more. Then you'll learn about Ethereum and smart contracts, and we'll cover Ethereum virtual machine (EVM) in detail. Next, you'll get acquainted with DApps and DAOs and see how they work. We'll also delve into the mechanisms of advanced smart contracts, taking a practical approach. You'll also learn how to develop your own cryptocurrency from scratch in order to understand the business behind ICO. Further on, you'll get to know the key concepts of the Solidity programming language, enabling you to build decentralized blockchain-based applications. We'll also look at enterprise use cases, where you'll build a decentralized microblogging site. At the end of this book, we discuss blockchain-as-a-service, the dark web marketplace, and various advanced topics so you can get well versed with the blockchain principles and ecosystem. Style and approach This comprehensive guide takes a practical approach by showing you how to implement Blockchain in different Enterprise use cases. You’ll quickly brush up on the basics of the blockchain database, then learn the advanced intricacies of smart contract development.

Get to grips with the essentials of deep learning by leveraging the power of Python About This Book ? Your one-stop solution to get started with the essentials of deep learning and neural network modeling ? Train different kinds of neural networks to tackle various problems in Natural Language Processing, computer vision, speech recognition, and more ? Covers popular Python libraries such as Tensorflow, Keras, and more, along with tips on training, deploying and optimizing your deep learning models in the best possible manner Who This Book Is For Aspiring data scientists and machine learning experts who have limited or no exposure to deep learning will find this book to be very useful. If you are looking for a resource that gets you up and running with the fundamentals of deep learning and neural networks, this book is for you. As the models in the book are trained using the popular Python-based libraries such as Tensorflow and Keras, it would be useful to have sound programming knowledge of Python. What You Will Learn ? Get to grips with the core concepts of deep learning and neural networks ? Set up deep learning library such as TensorFlow ? Fine-tune your deep learning models for NLP and Computer Vision applications ? Unify different information sources, such as images, text, and speech through deep learning ? Optimize and fine-tune your deep learning models for better performance ? Train a deep reinforcement learning model that plays a game better than humans ? Learn how to make your models get the best out of your GPU or CPU In Detail Deep Learning a trending topic in the field of Artificial Intelligence today and can be considered to be an advanced form of machine learning, which is quite tricky to master. This book will help you take your first steps in training efficient deep learning models and applying them in various practical scenarios. You will model, train, and deploy different kinds of neural networks such as Convolutional Neural Network, Recurrent Neural Network, and will see some of their applications in real-world domains including computer vision, natural language processing, speech recognition, and so on. You will build practical projects such as chatbots, implement reinforcement learning to build smart games, and develop expert systems for image captioning and processing. Popular Python library such as TensorFlow is used in this book to build the models. This book also covers solutions for different problems you might come across while training models, such as noisy datasets, small datasets, and more. This book does not assume any prior knowledge of deep learning. By the end of this book, you will have a firm understanding of the basics of deep learning and neural network modeling, along with their practical applications. Style and approach This step-by-step guide is filled with real-world practical examples and use cases to solve various deep learning problems.

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.

Build DIY wireless projects using the Raspberry Pi Zero W board About This Book ? Explore the functionalities of the Raspberry Pi Zero W with exciting projects ? Master the wireless features (and extend the use cases) of this $10 chip ? A project-based guide that will teach you to build simple yet exciting projects using the Raspberry Pi Zero W board Who This Book Is For If you are a hobbyist or an enthusiast and want to get your hands on the latest Raspberry Pi Zero W to build exciting wireless projects, then this book is for you. Some prior programming knowledge, with some experience in electronics, would be useful. What You Will Learn ? Set up a router and connect Raspberry Pi Zero W to the internet ? Create a two-wheel mobile robot and control it from your Android device ? Build an automated home bot assistant device ? Host your personal website with the help of Raspberry Pi Zero W ? Connect Raspberry Pi Zero to speakers to play your favorite music ? Set up a web camera connected to the Raspberry Pi Zero W and add another security layer to your home automation In Detail The Raspberry Pi has always been the go–to, lightweight ARM-based computer. The recent launch of the Pi Zero W has not disappointed its audience with its $10 release. "W" here stands for Wireless, denoting that the Raspberry Pi is solely focused on the recent trends for wireless tools and the relevant use cases. This is where our book—Raspberry Pi Zero W Wireless Projects—comes into its own. Each chapter will help you design and build a few DIY projects using the Raspberry Pi Zero W board. First, you will learn how to create a wireless decentralized chat service (client-client) using the Raspberry Pi's features?. Then you will make a simple two-wheel mobile robot and control it via your Android device over your local Wi-Fi network. Further, you will use the board to design a home bot that can be connected to plenty of devices in your home. The next two projects build a simple web streaming security layer using a web camera and portable speakers that will adjust the playlist according to your mood. You will also build a home server to host files and websites using the board. Towards the end, you will create free Alexa voice recognition software and an FPV Pi Camera, which can be used to monitor a system, watch a movie, spy on something, remotely control a drone, and more. By the end of this book, you will have developed the skills required to build exciting and complex projects with Raspberry Pi Zero W. Style and approach A step-by-step guide that will help you design and create simple yet exciting projects using the Raspberry Pi Zero W board.

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.

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.

Share code and assets across domains in Web applications with CORS About This Book ? A step-by-step guide but at a high level/fast pace. Not all steps are covered as a basic knowledge is assumed ? Provides a basic overview of the concepts but the focus is on providing the practical skills required to develop applications ? Focuses on providing practical examples Who This Book Is For Web developers have been limited by the Same Origin Policy and often wish they could spread their application across different domains. You know JavaScript and AJAX, and have run up against the Same Domain Policy, which is limiting your applications. What You Will Learn ? Why you need CORS: Bending the Same Origin Policy and basic CORS implementation, headers and XMLHttpRequest ? Creating proxies for CORS: Sometimes the header is not enough ? Security: vulnerabilities and how to secure your CORS application ? CORS implementations in Content Management systems ? Learn about CORS in Windows applications ? Take CORS on the Cloud ? Apply CORS in Node.js ? Best practices for CORS In Detail This book explains how to use CORS, including specific implementations for platforms such as Drupal, WordPress, IIS Server, ASP.NET, JBoss, Windows Azure, and Salesforce, as well as how to use CORS in the Cloud on Amazon AWS, YouTube, Mulesoft, and others. It examines limitations, security risks, and alternatives to CORS. It explores the W3C Specification and major developer documentation sources about CORS. It attempts to predict what kinds of extension to the CORS specification, or completely new techniques, will come in the future to address the limitations of CORS Web developers will learn how to share code and assets across domains with CORS. They will learn a variety of techniques that are rather similar in their method and syntax. The book is organized by similar types of framework and application, so it can be used as a reference. Developers will learn about special cases, such as when a proxy is necessary. And they will learn about some alternative techniques that achieve similar goals, and when they may be preferable to using CORS Style and approach A step-by-step guide filled with real-world applications

A practical book which will help the readers understand how the container ecosystem and OpenStack work together. About This Book ? Gets you acquainted with containerization in private cloud ? Learn to effectively manage and secure your containers in OpenStack ? Practical use cases on container deployment and management using OpenStack components Who This Book Is For This book is targeted towards cloud engineers, system administrators, or anyone from the production team who works on OpenStack cloud. This book act as an end to end guide for anyone who wants to start using the concept of containerization on private cloud. Some basic knowledge of Docker and Kubernetes will help. What You Will Learn ? Understand the role of containers in the OpenStack ecosystem ? Learn about containers and different types of container runtimes tools. ? Understand containerization in OpenStack with respect to the deployment framework, platform services, application deployment, and security ? Get skilled in using OpenStack to run your applications inside containers ? Explore the best practices of using containers in OpenStack. In Detail Containers are one of the most talked about technologies of recent times. They have become increasingly popular as they are changing the way we develop, deploy, and run software applications. OpenStack gets tremendous traction as it is used by many organizations across the globe and as containers gain in popularity and become complex, it’s necessary for OpenStack to provide various infrastructure resources for containers, such as compute, network, and storage. Containers in OpenStack answers the question, how can OpenStack keep ahead of the increasing challenges of container technology? You will start by getting familiar with container and OpenStack basics, so that you understand how the container ecosystem and OpenStack work together. To understand networking, managing application services and deployment tools, the book has dedicated chapters for different OpenStack projects: Magnum, Zun, Kuryr, Murano, and Kolla. Towards the end, you will be introduced to some best practices to secure your containers and COE on OpenStack, with an overview of using each OpenStack projects for different use cases. Style and approach An end to end guide for anyone who wants to start using the concept of containerization on private cloud.