Go beyond the basics and unleash the full power of QGIS 3.4 and 3.6 with practical, step-by-step examples Key Features * One-stop solution to all of your GIS needs * Master QGIS by learning about database integration, and geoprocessing tools * Learn about the new and updated Processing toolbox and perform spatial analysis Book Description QGIS is an open source solution to GIS and widely used by GIS professionals all over the world. It is the leading alternative to proprietary GIS software. Although QGIS is described as intuitive, it is also, by default, complex. Knowing which tools to use and how to apply them is essential to producing valuable deliverables on time. Starting with a refresher on the QGIS basics and getting you acquainted with the latest QGIS 3.6 updates, this book will take you all the way through to teaching you how to create a spatial database and a GeoPackage. Next, you will learn how to style raster and vector data by choosing and managing different colors. The book will then focus on processing raster and vector data. You will be then taught advanced applications, such as creating and editing vector data. Along with that, you will also learn about the newly updated Processing Toolbox, which will help you develop the advanced data visualizations. The book will then explain to you the graphic modeler, how to create QGIS plugins with PyQGIS, and how to integrate Python analysis scripts with QGIS. By the end of the book, you will understand how to work with all aspects of QGIS and will be ready to use it for any type of GIS work. What you will learn * Create and manage a spatial database * Get to know advanced techniques to style GIS data * Prepare both vector and raster data for processing * Add heat maps, live layer effects, and labels to your maps * Master LAStools and GRASS integration with the Processing Toolbox * Edit and repair topological data errors * Automate workflows with batch processing and the QGIS Graphical Modeler * Integrate Python scripting into your data processing workflows * Develop your own QGIS plugins Who this book is for If you are a GIS professional, a consultant, a student, or perhaps a fast learner who wants to go beyond the basics of QGIS, then this book is for you. It will prepare you to realize the full potential of QGIS.

Gain basic skills in network forensics and learn how to apply them effectively Key Features * Investigate network threats with ease * Practice forensics tasks such as intrusion detection, network analysis, and scanning * Learn forensics investigation at the network level Book Description Network forensics is a subset of digital forensics that deals with network attacks and their investigation. In the era of network attacks and malware threat, it’s now more important than ever to have skills to investigate network attacks and vulnerabilities. Hands-On Network Forensics starts with the core concepts within network forensics, including coding, networking, forensics tools, and methodologies for forensic investigations. You’ll then explore the tools used for network forensics, followed by understanding how to apply those tools to a PCAP file and write the accompanying report. In addition to this, you will understand how statistical flow analysis, network enumeration, tunneling and encryption, and malware detection can be used to investigate your network. Towards the end of this book, you will discover how network correlation works and how to bring all the information from different types of network devices together. By the end of this book, you will have gained hands-on experience of performing forensics analysis tasks. What you will learn * Discover and interpret encrypted traffic * Learn about various protocols * Understand the malware language over wire * Gain insights into the most widely used malware * Correlate data collected from attacks * Develop tools and custom scripts for network forensics automation Who this book is for The book targets incident responders, network engineers, analysts, forensic engineers and network administrators who want to extend their knowledge from the surface to the deep levels of understanding the science behind network protocols, critical indicators in an incident and conducting a forensic search over the wire.

Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks. Key Features * Train your own models for effective prediction, using high-level Keras API * Perform supervised and unsupervised machine learning and learn advanced techniques such as training neural networks * Get acquainted with some new practices introduced in TensorFlow 2.0 Alpha Book Description TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks. After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains. By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques. What you will learn * Use tf.Keras for fast prototyping, building, and training deep learning neural network models * Easily convert your TensorFlow 1.12 applications to TensorFlow 2.0-compatible files * Use TensorFlow to tackle traditional supervised and unsupervised machine learning applications * Understand image recognition techniques using TensorFlow * Perform neural style transfer for image hybridization using a neural network * Code a recurrent neural network in TensorFlow to perform text-style generation Who this book is for Data scientists, machine learning developers, and deep learning enthusiasts looking to quickly get started with TensorFlow 2 will find this book useful. Some Python programming experience with version 3.6 or later, along with a familiarity with Jupyter notebooks will be an added advantage. Exposure to machine learning and neural network techniques would also be helpful.

Solve real-world data problems with R and machine learning Key Features * Third edition of the bestselling, widely acclaimed R machine learning book, updated and improved for R 3.5 and beyond * Harness the power of R to build flexible, effective, and transparent machine learning models * Learn quickly with a clear, hands-on guide by experienced machine learning teacher and practitioner, Brett Lantz Book Description Machine learning, at its core, is concerned with transforming data into actionable knowledge. R offers a powerful set of machine learning methods to quickly and easily gain insight from your data. Machine Learning with R, Third Edition provides a hands-on, readable guide to applying machine learning to real-world problems. Whether you are an experienced R user or new to the language, Brett Lantz teaches you everything you need to uncover key insights, make new predictions, and visualize your findings. This new 3rd edition updates the classic R data science book with newer and better libraries, advice on ethical and bias issues in machine learning, and an introduction to deep learning. Find powerful new insights in your data; discover machine learning with R. What you will learn * Discover the origins of machine learning and how exactly a computer learns by example * Prepare your data for machine learning work with the R programming language * Classify important outcomes using nearest neighbor and Bayesian methods * Predict future events using decision trees, rules, and support vector machines * Forecast numeric data and estimate financial values using regression methods * Model complex processes with artificial neural networks — the basis of deep learning * Avoid bias in machine learning models * Evaluate your models and improve their performance * Connect R to SQL databases and emerging big data technologies such as Spark, H2O, and TensorFlow Who this book is for Data scientists, students, and other practitioners who want a clear, accessible guide to machine learning with R.

Make use of hands-on recipes for many tasks that are typically encountered in both the on-premises as well as the cloud world. Key Features * A recipe-based guide to help you build effective administrative solutions * Gain hands-on experience with the newly added features of PowerShell Core * Manage critical business environments with professional scripting practices Book Description This book will follow a recipe-based approach and start off with an introduction to the fundamentals of PowerShell, and explaining how to install and run it through simple examples. Next, you will learn how to use PowerShell to access and manipulate data and how to work with different streams as well. You will also explore the object model which will help with regard to PowerShell function deployment. Going forward, you will get familiar with the pipeline in its different use cases. The next set of chapters will deal with the different ways of accessing data in PowerShell. You will also learn to automate various tasks in Windows and Linux using PowerShell Core, as well as explore Windows Server. Later, you will be introduced to Remoting in PowerShell Core and Just Enough Administration concept. The last set of chapters will help you understand the management of a private and public cloud with PowerShell Core. You will also learn how to access web services and explore the high-performance scripting methods. By the end of this book, you will gain the skills to manage complex tasks effectively along with increasing the performance of your environment. What you will learn * Leverage cross-platform interaction with systems * Make use of the PowerShell recipes for frequent tasks * Get a better understanding of the inner workings of PowerShell * Understand the compatibility of built-in Windows modules with PowerShell Core * Learn best practices associated with PowerShell scripting * Avoid common pitfalls and mistakes Who this book is for This book will be for windows administrators who want to enhance their PowerShell scripting skills to the next level. System administrators wanting to automate common to complex tasks with PowerShell scripts would benefit from this book. Prior understanding on PowerShell would be necessary.

Learn and use the design patterns and best practices in Spring to solve common design problems and build user-friendly microservices Key Features *Study the benefits of using the right design pattern in your toolkit *Manage your code easily with Spring's dependency injection pattern *Explore the features of Docker and Mesos to build successful microservices Book Description Getting Started with Spring Microservices begins with an overview of the Spring Framework 5.0, its design patterns, and its guidelines that enable you to implement responsive microservices at scale. You will learn how to use GoF patterns in application design. You will understand the dependency injection pattern, which is the main principle behind the decoupling process of the Spring Framework and makes it easier to manage your code. Then, you will learn how to use proxy patterns in aspect-oriented programming and remoting. Moving on, you will understand the JDBC template patterns and their use in abstracting database access. After understanding the basics, you will move on to more advanced topics, such as reactive streams and concurrency. Written to the latest specifications of Spring that focuses on Reactive Programming, the Learning Path teaches you how to build modern, internet-scale Java applications in no time. Next, you will understand how Spring Boot is used to deploying serverless autonomous services by removing the need to have a heavyweight application server. You’ll also explore ways to deploy your microservices to Docker and managing them with Mesos. By the end of this Learning Path, you will have the clarity and confidence for implementing microservices using Spring Framework. This Learning Path includes content from the following Packt products: *Spring 5 Microservices by Rajesh R V *Spring 5 Design Patterns by Dinesh Rajput What you will learn *Develop applications using dependency injection patterns *Build web applications using traditional Spring MVC patterns *Utilize the reactive programming pattern to build reactive web apps *Learn concurrency and handle multiple connections inside a web server *Use Spring Boot and Spring Cloud to develop microservices *Leverage reactive programming to build cloud-native applications Who this book is for Getting Started with Spring Microservices is ideal for Spring developers who want to use design patterns to solve common design problems and build cloud-ready, Internet-scale applications, and simple RESTful services.

Create apps in C++ and leverage its latest features using modern programming techniques. Key Features *Develop strong C++ skills to build a variety of applications *Explore features of C++17, such as containers, algorithms, and threads *Grasp the standard support for threading and concurrency and use them in basic daily tasks Book Description C++ is one of the most widely used programming languages. It is fast, flexible, and used to solve many programming problems. This Learning Path gives you an in-depth and hands-on experience of working with C++, using the latest recipes and understanding most recent developments. You will explore C++ programming constructs by learning about language structures, functions, and classes, which will help you identify the execution flow through code. You will also understand the importance of the C++ standard library as well as memory allocation for writing better and faster programs. Modern C++: Efficient and Scalable Application Development deals with the challenges faced with advanced C++ programming. You will work through advanced topics such as multithreading, networking, concurrency, lambda expressions, and many more recipes. By the end of this Learning Path, you will have all the skills to become a master C++ programmer. This Learning Path includes content from the following Packt products: *Beginning C++ Programming by Richard Grimes *Modern C++ Programming Cookbook by Marius Bancila *The Modern C++ Challenge by Marius Bancila What you will learn *Become familiar with the structure of C++ projects *Identify the main structures in the language: functions and classes *Learn to debug your programs *Leverage C++ features to obtain increased robustness and performance *Explore functions and callable objects with a focus on modern features *Serialize and deserialize JSON and XML data *Create client-server applications that communicate over TCP/IP *Use design patterns to solve real-world problems Who this book is for This Learning Path is designed for developers who want to gain a solid foundation in C++. The desire to learn how to code in C++ is all you need to get started with this Learning Path

Integrate your React applications with React to build efficient web services. Key Features * Learn React by building applications with Create React App * Create interactive UIs exploring the latest feature of CRA 2.0 * Build Progressive Web Applications for a more seamless web Book Description If you're a power user and you aren’t happy always reusing default configurations, from previous applications with each new application, then all you need is Create React App (CRA), a tool in the React ecosystem designed to help you create boilerplate code for building a web frontend. This book will help you use CRA to write React programs without significant configuration-related difficulties. With this quick start guide, you will integrate your applications with React to build efficient professional web services.You will learn to design UIs with the features of CRA and template your React applications. By the end of the book, you will be sufficiently skilled to be able to build faster and effective React apps using CRA. What you will learn * Become familiar with React by building applications with Create React App * Make your frontend development hassle free * Create interactive UIs exploring the latest features of CRA 2 * Build modern, React projects with, SASS,and progressive web applications * Develop proxy backend servers and simulate interaction with a full backend * Keep your application fully tested and maintain confidence in your project Who this book is for The book is intended for the web developers who want to jump into building great frontend with React using easy templating solutions.

Build your Machine Learning portfolio by creating 6 cutting-edge Artificial Intelligence projects using neural networks in Python Key Features * Discover neural network architectures (like CNN and LSTM) that are driving recent advancements in AI * Build expert neural networks in Python using popular libraries such as Keras * Includes projects such as object detection, face identification, sentiment analysis, and more Book Description Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio. What you will learn * Learn various neural network architectures and its advancements in AI * Master deep learning in Python by building and training neural network * Master neural networks for regression and classification * Discover convolutional neural networks for image recognition * Learn sentiment analysis on textual data using Long Short-Term Memory * Build and train a highly accurate facial recognition security system Who this book is for This book is a perfect match for data scientists, machine learning engineers, and deep learning enthusiasts who wish to create practical neural network projects in Python. Readers should already have some basic knowledge of machine learning and neural networks.

A comprehensive guide to mastering the most advanced Hadoop 3 concepts Key Features * Get to grips with the newly introduced features and capabilities of Hadoop 3 * Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem * Sharpen your Hadoop skills with real-world case studies and code Book Description Apache Hadoop is one of the most popular big data solutions for distributed storage and for processing large chunks of data. With Hadoop 3, Apache promises to provide a high-performance, more fault-tolerant, and highly efficient big data processing platform, with a focus on improved scalability and increased efficiency. With this guide, you’ll understand advanced concepts of the Hadoop ecosystem tool. You’ll learn how Hadoop works internally, study advanced concepts of different ecosystem tools, discover solutions to real-world use cases, and understand how to secure your cluster. It will then walk you through HDFS, YARN, MapReduce, and Hadoop 3 concepts. You’ll be able to address common challenges like using Kafka efficiently, designing low latency, reliable message delivery Kafka systems, and handling high data volumes. As you advance, you’ll discover how to address major challenges when building an enterprise-grade messaging system, and how to use different stream processing systems along with Kafka to fulfil your enterprise goals. By the end of this book, you’ll have a complete understanding of how components in the Hadoop ecosystem are effectively integrated to implement a fast and reliable data pipeline, and you’ll be equipped to tackle a range of real-world problems in data pipelines. What you will learn * Gain an in-depth understanding of distributed computing using Hadoop 3 * Develop enterprise-grade applications using Apache Spark, Flink, and more * Build scalable and high-performance Hadoop data pipelines with security, monitoring, and data governance * Explore batch data processing patterns and how to model data in Hadoop * Master best practices for enterprises using, or planning to use, Hadoop 3 as a data platform * Understand security aspects of Hadoop, including authorization and authentication Who this book is for If you want to become a big data professional by mastering the advanced concepts of Hadoop, this book is for you. You’ll also find this book useful if you’re a Hadoop professional looking to strengthen your knowledge of the Hadoop ecosystem. Fundamental knowledge of the Java programming language and basics of Hadoop is necessary to get started with this book.

Plug the gaps in your network’s infrastructure with resilient network security models Key Features * Develop a cost-effective and end-to-end vulnerability management program * Explore best practices for vulnerability scanning and risk assessment * Understand and implement network enumeration with Nessus and Network Mapper (Nmap) Book Description Digitization drives technology today, which is why it’s so important for organizations to design security mechanisms for their network infrastructures. Analyzing vulnerabilities is one of the best ways to secure your network infrastructure. This Learning Path begins by introducing you to the various concepts of network security assessment, workflows, and architectures. You will learn to employ open source tools to perform both active and passive network scanning and use these results to analyze and design a threat model for network security. With a firm understanding of the basics, you will then explore how to use Nessus and Nmap to scan your network for vulnerabilities and open ports and gain back door entry into a network. As you progress through the chapters, you will gain insights into how to carry out various key scanning tasks, including firewall detection, OS detection, and access management to detect vulnerabilities in your network. By the end of this Learning Path, you will be familiar with the tools you need for network scanning and techniques for vulnerability scanning and network protection. This Learning Path includes content from the following Packt books: * Network Scanning Cookbook by Sairam Jetty * Network Vulnerability Assessment by Sagar Rahalkar What you will learn * Explore various standards and frameworks for vulnerability assessments and penetration testing * Gain insight into vulnerability scoring and reporting * Discover the importance of patching and security hardening * Develop metrics to measure the success of a vulnerability management program * Perform configuration audits for various platforms using Nessus * Write custom Nessus and Nmap scripts on your own * Install and configure Nmap and Nessus in your network infrastructure * Perform host discovery to identify network devices Who this book is for This Learning Path is designed for security analysts, threat analysts, and security professionals responsible for developing a network threat model for an organization. Professionals who want to be part of a vulnerability management team and implement an end-to-end robust vulnerability management program will also find this Learning Path useful.

Create a real-world application in Go and explore various frameworks and methodologies for full-stack development Key Features * Organize your isomorphic codebase to enhance the maintainability of your application * Build web APIs and middleware in the Go language by making use of the popular Gin framework * Implement real-time web application functionality with WebSockets Book Description The Go programming language has been rapidly adopted by developers for building web applications. With its impressive performance and ease of development, Go enjoys the support of a wide variety of open source frameworks, for building scalable and high-performant web services and apps. Hands-On Full Stack Development with Go is a comprehensive guide that covers all aspects of full stack development with Go. This clearly written, example-rich book begins with a practical exposure to Go development and moves on to build a frontend with the popular React framework. From there, you will build RESTful web APIs utilizing the Gin framework. After that, we will dive deeper into important software backend concepts, such as connecting to the database via an ORM, designing routes for your services, securing your services, and even charging credit cards via the popular Stripe API. We will also cover how to test, and benchmark your applications efficiently in a production environment. In the concluding chapters, we will cover isomorphic developments in pure Go by learning about GopherJS. As you progress through the book, you'll gradually build a musical instrument online store application from scratch. By the end of the book, you will be confident in taking on full stack web applications in Go. What you will learn * Understand Go programming by building a real-world application * Learn the React framework to develop a frontend for your application * Understand isomorphic web development utilizing the GopherJS framework * Explore methods to write RESTful web APIs in Go using the Gin framework * Learn practical topics such as ORM layers, secure communications, and Stripe's API * Learn methods to benchmark and test web APIs in Go Who this book is for Hands-On Full Stack Development with Go will appeal to developers who are looking to start building amazing full stack web applications in Go. Basic knowhow of Go language and JavaScript is expected. The book targets web developers who are looking to move to the Go language.

Learn how to build complete machine learning systems with IBM Cloud and Watson Machine learning services Key Features * Implement data science and machine learning techniques to draw insights from real-world data * Understand what IBM Cloud platform can help you to implement cognitive insights within applications * Understand the role of data representation and feature extraction in any machine learning system Book Description IBM Cloud is a collection of cloud computing services for data analytics using machine learning and artificial intelligence (AI). This book is a complete guide to help you become well versed with machine learning on the IBM Cloud using Python. Hands-On Machine Learning with IBM Watson starts with supervised and unsupervised machine learning concepts, in addition to providing you with an overview of IBM Cloud and Watson Machine Learning. You'll gain insights into running various techniques, such as K-means clustering, K-nearest neighbor (KNN), and time series prediction in IBM Cloud with real-world examples. The book will then help you delve into creating a Spark pipeline in Watson Studio. You will also be guided through deep learning and neural network principles on the IBM Cloud using TensorFlow. With the help of NLP techniques, you can then brush up on building a chatbot. In later chapters, you will cover three powerful case studies, including the facial expression classification platform, the automated classification of lithofacies, and the multi-biometric identity authentication platform, helping you to become well versed with these methodologies. By the end of this book, you will be ready to build efficient machine learning solutions on the IBM Cloud and draw insights from the data at hand using real-world examples. What you will learn * Understand key characteristics of IBM machine learning services * Run supervised and unsupervised techniques in the cloud * Understand how to create a Spark pipeline in Watson Studio * Implement deep learning and neural networks on the IBM Cloud with TensorFlow * Create a complete, cloud-based facial expression classification solution * Use biometric traits to build a cloud-based human identification system Who this book is for This beginner-level book is for data scientists and machine learning engineers who want to get started with IBM Cloud and its machine learning services using practical examples. Basic knowledge of Python and some understanding of machine learning will be useful.

Leverage the power of MongoDB 4.x to build and administer fault-tolerant database applications Key Features * Master the new features and capabilities of MongoDB 4.x * Implement advanced data modeling, querying, and administration techniques in MongoDB * Includes rich case-studies and best practices followed by expert MongoDB developers Book Description MongoDB is the best platform for working with non-relational data and is considered to be the smartest tool for organizing data in line with business needs. The recently released MongoDB 4.x supports ACID transactions and makes the technology an asset for enterprises across the IT and fintech sectors. This book provides expertise in advanced and niche areas of managing databases (such as modeling and querying databases) along with various administration techniques in MongoDB, thereby helping you become a successful MongoDB expert. The book helps you understand how the newly added capabilities function with the help of some interesting examples and large datasets. You will dive deeper into niche areas such as high-performance configurations, optimizing SQL statements, configuring large-scale sharded clusters, and many more. You will also master best practices in overcoming database failover, and master recovery and backup procedures for database security. By the end of the book, you will have gained a practical understanding of administering database applications both on premises and on the cloud; you will also be able to scale database applications across all servers. What you will learn * Perform advanced querying techniques such as indexing and expressions * Configure, monitor, and maintain a highly scalable MongoDB environment * Master replication and data sharding to optimize read/write performance * Administer MongoDB-based applications on premises or on the cloud * Integrate MongoDB with big data sources to process huge amounts of data * Deploy MongoDB on Kubernetes containers * Use MongoDB in IoT, mobile, and serverless environments Who this book is for This book is ideal for MongoDB developers and database administrators who wish to become successful MongoDB experts and build scalable and fault-tolerant applications using MongoDB. It will also be useful for database professionals who wish to become certified MongoDB professionals. Some understanding of MongoDB and basic database concepts is required to get the most out of this book.

A practical guide for developing end-to-end serverless microservices in Python for developers, DevOps, and architects. Key Features * Create a secure, cost-effective, and scalable serverless data API * Use identity management and authentication for a user-specific and secure web application * Go beyond traditional web hosting to explore the full range of cloud hosting options Book Description Over the last few years, there has been a massive shift from monolithic architecture to microservices, thanks to their small and independent deployments that allow increased flexibility and agile delivery. Traditionally, virtual machines and containers were the principal mediums for deploying microservices, but they involved a lot of operational effort, configuration, and maintenance. More recently, serverless computing has gained popularity due to its built-in autoscaling abilities, reduced operational costs, and increased productivity. Building Serverless Microservices in Python begins by introducing you to serverless microservice structures. You will then learn how to create your first serverless data API and test your microservice. Moving on, you'll delve into data management and work with serverless patterns. Finally, the book introduces you to the importance of securing microservices. By the end of the book, you will have gained the skills you need to combine microservices with serverless computing, making their deployment much easier thanks to the cloud provider managing the servers and capacity planning. What you will learn * Discover what microservices offer above and beyond other architectures * Create a serverless application with AWS * Gain secure access to data and resources * Run tests on your configuration and code * Create a highly available serverless microservice data API * Build, deploy, and run your serverless configuration and code Who this book is for If you are a developer with basic knowledge of Python and want to learn how to build, test, deploy, and secure microservices, then this book is for you. No prior knowledge of building microservices is required.

Your one-stop guide to learning and implementing artificial neural networks with Keras effectively Key Features * Design and create neural network architectures on different domains using Keras * Integrate neural network models in your applications using this highly practical guide * Get ready for the future of neural networks through transfer learning and predicting multi network models Book Description Neural networks are used to solve a wide range of problems in different areas of AI and deep learning. Hands-On Neural Networks with Keras will start with teaching you about the core concepts of neural networks. You will delve into combining different neural network models and work with real-world use cases, including computer vision, natural language understanding, synthetic data generation, and many more. Moving on, you will become well versed with convolutional neural networks (CNNs), recurrent neural networks (RNNs), long short-term memory (LSTM) networks, autoencoders, and generative adversarial networks (GANs) using real-world training datasets. We will examine how to use CNNs for image recognition, how to use reinforcement learning agents, and many more. We will dive into the specific architectures of various networks and then implement each of them in a hands-on manner using industry-grade frameworks. By the end of this book, you will be highly familiar with all prominent deep learning models and frameworks, and the options you have when applying deep learning to real-world scenarios and embedding artificial intelligence as the core fabric of your organization. What you will learn * Understand the fundamental nature and workflow of predictive data modeling * Explore how different types of visual and linguistic signals are processed by neural networks * Dive into the mathematical and statistical ideas behind how networks learn from data * Design and implement various neural networks such as CNNs, LSTMs, and GANs * Use different architectures to tackle cognitive tasks and embed intelligence in systems * Learn how to generate synthetic data and use augmentation strategies to improve your models * Stay on top of the latest academic and commercial developments in the field of AI Who this book is for This book is for machine learning practitioners, deep learning researchers and AI enthusiasts who are looking to get well versed with different neural network architecture using Keras. Working knowledge of Python programming language is mandatory.

Step through loading GIS data, creating GIS data, styling GIS and making maps with QGIS following a simple narrative that will allow you to build confidence as you progress. Key Features * Work with GIS data, a step by step guide from creation to making a map * Perform geoprocessing tasks and automate them using model builder * Explore a range of features in QGIS 3.4, discover the power behind open source desktop GIS Book Description QGIS is a user friendly, open source geographic information system (GIS). The popularity of open source GIS and QGIS, in particular, has been growing rapidly over the last few years. This book is designed to help beginners learn about all the tools required to use QGIS 3.4. This book will provide you with clear, step-by-step instructions to help you apply your GIS knowledge to QGIS. You begin with an overview of QGIS 3.4 and its installation. You will learn how to load existing spatial data and create vector data from scratch. You will then be creating styles and labels for maps. The final two chapters demonstrate the Processing toolbox and include a brief investigation on how to extend QGIS. Throughout this book, we will be using the GeoPackage format, and we will also discuss how QGIS can support many different types of data. Finally, you will learn where to get help and how to become engaged with the GIS community. What you will learn * Use existing data to interact with the canvas via zoom/pan/selection * Create vector data and a GeoPackage and build a simple project around it * Style data, both vector and raster data, using the Layer Styling Panel * Design, label, save, and export maps using the data you have created * Analyze spatial queries using the Processing toolbox * Expand QGIS with the help of plugins, model builder, and the command line Who this book is for If you know the basic functions and processes of GIS, and want to learn to use QGIS to analyze geospatial data and create rich mapping applications, then this is the book for you.

Improve your React Native mobile development skills or transition from web development to mobile development with this practical solution-packed guide Key Features * Learn strategies and techniques to face challenges in React Native mobile development head-on * Leverage the best ways to use iOS and Android for React Native development while maximizing code reuse and cohesion * Build engaging, performant user experiences with React Native Book Description If you are a developer looking to create mobile applications with maximized code reusability and minimized cost, then React Native is here to help. With this practical guide, you will be able to build attractive UIs, tackle common mobile development-related issues, and achieve improved performance in mobile environments. This book starts with common techniques for React Native customization and helps you set up your development platforms. Over the course of the book, a wide variety of step-by-step recipes are designed with both built-in React Native and custom third-party components that you will create, style, and animate. You will create real-world browser-based authentication, build a fully functional audio player, and integrate with Google maps. You will also explore different strategies for working with data, including leveraging the popular Redux library and optimizing your app’s dataflow. You will then get an introduction to writing native device functionality for new and already existing native projects. Finally, you will learn how app deployment works, and tips and tricks for writing performant code. By the end of the book, you'll have gained enough knowledge to build full iOS and Android applications using React Native. What you will learn * Build UI features and components using React Native * Create advanced animations for UI components * Develop universal apps that run on phones and tablets * Leverage Redux to manage application flow and data * Expose both custom native UI components and application logic to React Native * Employ open-source third-party plugins to create React Native apps more efficiently Who this book is for If you're a JavaScript developer looking for a practical guide with step-by-step tutorials for developing feature rich mobile apps using React Native, then this book is for you. Though not required, some experience working with React will help you more easily understand the React Native concepts covered in this book. While React Native development can be done on a Windows machine, certain aspects, such as running your apps on iOS devices and in the iOS simulator, or editing native code with Xcode, can only be done with a Mac.

A quick start guide to visualize your Elasticsearch data Key Features * Your hands-on guide to visualizing the Elasticsearch data as well as navigating the Elastic stack * Work with different Kibana plugins and create effective machine learning jobs using Kibana * Build effective dashboards and reports without any hassle Book Description The Elastic Stack is growing rapidly and, day by day, additional tools are being added to make it more effective. This book endeavors to explain all the important aspects of Kibana, which is essential for utilizing its full potential. This book covers the core concepts of Kibana, with chapters set out in a coherent manner so that readers can advance their learning in a step-by-step manner. The focus is on a practical approach, thereby enabling the reader to apply those examples in real time for a better understanding of the concepts and to provide them with the correct skills in relation to the tool. With its succinct explanations, it is quite easy for a reader to use this book as a reference guide for learning basic to advanced implementations of Kibana. The practical examples, such as the creation of Kibana dashboards from CSV data, application RDBMS data, system metrics data, log file data, APM agents, and search results, can provide readers with a number of different drop-off points from where they can fetch any type of data into Kibana for the purpose of analysis or dashboarding. What you will learn * Explore how Logstash is configured to fetch CSV data * Understand how to create index patterns in Kibana * Become familiar with how to apply filters on data * Discover how to create ML jobs * Explore how to analyze APM data from APM agents * Get to grips with how to save, share, inspect, and edit visualizations * Understand how to find an anomaly in data Who this book is for Kibana 7 Quick Start Guide is for developers new to Kibana who want to learn the fundamentals of using the tool for visualization, as well as existing Elastic developers.

Become proficient in designing, developing and deploying effective software systems using the advanced constructs of Rust Key Features * Improve your productivity using the latest version of Rust and write simpler and easier code * Understand Rust’s immutability and ownership principle, expressive type system, safe concurrency * Deep dive into the new doamins of Rust like WebAssembly, Networking and Command line tools Book Description Rust is an empowering language that provides a rare combination of safety, speed, and zero-cost abstractions. Mastering Rust – Second Edition is filled with clear and simple explanations of the language features along with real-world examples, showing you how you can build robust, scalable, and reliable programs. This second edition of the book improves upon the previous one and touches on all aspects that make Rust a great language. We have included the features from latest Rust 2018 edition such as the new module system, the smarter compiler, helpful error messages, and the stable procedural macros. You’ll learn how Rust can be used for systems programming, network programming, and even on the web. You’ll also learn techniques such as writing memory-safe code, building idiomatic Rust libraries, writing efficient asynchronous networking code, and advanced macros. The book contains a mix of theory and hands-on tasks so you acquire the skills as well as the knowledge, and it also provides exercises to hammer the concepts in. After reading this book, you will be able to implement Rust for your enterprise projects, write better tests and documentation, design for performance, and write idiomatic Rust code. What you will learn * Write generic and type-safe code by using Rust’s powerful type system * How memory safety works without garbage collection * Know the different strategies in error handling and when to use them * Learn how to use concurrency primitives such as threads and channels * Use advanced macros to reduce boilerplate code * Create efficient web applications with the Actix-web framework * Use Diesel for type-safe database interactions in your web application Who this book is for The book is aimed at beginner and intermediate programmers who already have familiarity with any imperative language and have only heard of Rust as a new language. If you are a developer who wants to write robust, efficient and maintainable software systems and want to become proficient with Rust, this book is for you. It starts by giving a whirlwind tour of the important concepts of Rust and covers advanced features of the language in subsequent chapters using code examples that readers will find useful to advance their knowledge.

A hands-on guide to Android programming with Spring MVC, Spring Boot, and Spring Security Key Features * Build native Android applications with Spring for Android * Explore Reactive programming, concurrency, and multithreading paradigms for building fast and efficient applications * Write more expressive and robust code with Kotlin using its coroutines and other latest features Book Description As the new official language for Android, Kotlin is attracting new as well as existing Android developers. As most developers are still working with Java and want to switch to Kotlin, they find a combination of these two appealing. This book addresses this interest by bringing together Spring, a widely used Java SE framework for building enterprise-grade applications, and Kotlin. Learn Spring for Android Application Development will guide you in leveraging some of the powerful modules of the Spring Framework to build lightweight and robust Android apps using Kotlin. You will work with various modules, such as Spring AOP, Dependency Injection, and Inversion of Control, to develop applications with better dependency management. You’ll also explore other modules of the Spring Framework, such as Spring MVC, Spring Boot, and Spring Security. Each chapter has practice exercises at the end for you to assess your learning. By the end of the book, you will be fully equipped to develop Android applications with Spring technologies. What you will learn * Get to grips with the basics of the Spring Framework * Write web applications using the Spring Framework with Kotlin * Develop Android apps with Kotlin * Connect a RESTful web service with your app using Retrofilt * Understand JDBC, JPA, MySQL for Spring and SQLite Room for Android * Explore Spring Security fundamentals, Basic Authentication, and OAuth2 * Delve into Concurrency and Reactive programming using Kotlin * Develop testable applications with Spring and Android Who this book is for If you’re an aspiring Android developer or an existing developer who wants to learn how to use Spring to build robust Android applications in Kotlin, this book is for you. Though not necessary, basic knowledge of Spring will assist with understanding key concepts covered in this book.