Practically and deeply understand concurrency in Python to write efficient programs About This Book ? Build highly efficient, robust, and concurrent applications ? Work through practical examples that will help you address the challenges of writing concurrent code ? Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available Who This Book Is For This book is for Python developers who would like to get started with concurrent programming. Readers are expected to have a working knowledge of the Python language, as this book will build on these fundamentals concepts. What You Will Learn ? Explore the concept of threading and multiprocessing in Python ? Understand concurrency with threads ? Manage exceptions in child threads ? Handle the hardest part in a concurrent system — shared resources ? Build concurrent systems with Communicating Sequential Processes (CSP) ? Maintain all concurrent systems and master them ? Apply reactive programming to build concurrent systems ? Use GPU to solve specific problems In Detail Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices. Style and approach This easy-to-follow guide teaches you new practices and techniques to optimize your code, and then moves toward more advanced ways to effectively write efficient Python code. Small and simple practical examples will help you test the concepts yourself, and you will be able to easily adapt them for any application.

Build smart, efficient, and fast enterprise-grade web implementation of the microservices architecture that can be easily scaled. About This Book ? Write easy-to-maintain lean and clean code with Kotlin for developing better microservices ? Scale your Microserivces in your own cloud with Docker and Docker Swarm ? Explore Spring 5 functional reactive web programming with Spring WebFlux Who This Book Is For If you are a Kotlin developer with a basic knowledge of microservice architectures and now want to effectively implement these services on enterprise-level web applications, then this book is for you What You Will Learn ? Understand microservice architectures and principles ? Build microservices in Kotlin using Spring Boot 2.0 and Spring Framework 5.0 ? Create reactive microservices that perform non-blocking operations with Spring WebFlux ? Use Spring Data to get data reactively from MongoDB ? Test effectively with JUnit and Kotlin ? Create cloud-native microservices with Spring Cloud ? Build and publish Docker images of your microservices ? Scaling microservices with Docker Swarm ? Monitor microservices with JMX ? Deploy microservices in OpenShift Online In Detail With Google's inclusion of first-class support for Kotlin in their Android ecosystem, Kotlin's future as a mainstream language is assured. Microservices help design scalable, easy-to-maintain web applications; Kotlin allows us to take advantage of modern idioms to simplify our development and create high-quality services. With 100% interoperability with the JVM, Kotlin makes working with existing Java code easier. Well-known Java systems such as Spring, Jackson, and Reactor have included Kotlin modules to exploit its language features. This book guides the reader in designing and implementing services, and producing production-ready, testable, lean code that's shorter and simpler than a traditional Java implementation. Reap the benefits of using the reactive paradigm and take advantage of non-blocking techniques to take your services to the next level in terms of industry standards. You will consume NoSQL databases reactively to allow you to create high-throughput microservices. Create cloud-native microservices that can run on a wide range of cloud providers, and monitor them. You will create Docker containers for your microservices and scale them. Finally, you will deploy your microservices in OpenShift Online. Style and approach This book guides the reader in designing and implementing services, achieving production- ready, testable, easy-to-maintain, lean code that's shorter and simpler than a traditional Java implementation.

Get more control of your applications performances in development and production and know how to meet your Service Level Agreement on critical microservices. About This Book ? Learn how to write a JavaEE application with performance constraints (Service Level Agreement—SLA) leveraging the platform ? Learn how to identify bottlenecks and hotspots in your application to fix them ? Ensure that you are able to continuously control your performance in production and during development Who This Book Is For If you're a Java developer looking to improve the performance of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Identify performance bottlenecks in an application ? Locate application hotspots using performance tools ? Understand the work done under the hood by EE containers and its impact on performance ? Identify common patterns to integrate with Java EE applications ? Implement transparent caching on your applications ? Extract more information from your applications using Java EE without modifying existing code ? Ensure constant performance and eliminate regression In Detail The ease with which we write applications has been increasing, but with this comes the need to address their performance. A balancing act between easily implementing complex applications and keeping their performance optimal is a present-day need. In this book, we explore how to achieve this crucial balance while developing and deploying applications with Java EE 8. The book starts by analyzing various Java EE specifications to identify those potentially affecting performance adversely. Then, we move on to monitoring techniques that enable us to identify performance bottlenecks and optimize performance metrics. Next, we look at techniques that help us achieve high performance: memory optimization, concurrency, multi-threading, scaling, and caching. We also look at fault tolerance solutions and the importance of logging. Lastly, you will learn to benchmark your application and also implement solutions for continuous performance evaluation. By the end of the book, you will have gained insights into various techniques and solutions that will help create high-performance applications in the Java EE 8 environment. Style and approach This book will cover vital concepts implemented through a sample application built throughout the book. This will enable you to apply these concepts to suit your software requirements.

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

A comprehensive guide to mastering the art of preventing your Linux system from getting compromised. About This Book ? Leverage this guide to confidently deliver a system that reduces the risk of being hacked ? Perform a number of advanced Linux security techniques such as network service detection, user authentication, controlling special permissions, encrypting file systems, and much more ? Master the art of securing a Linux environment with this end-to-end practical guide Who This Book Is For If you are a systems administrator or a network engineer interested in making your Linux environment more secure, then this book is for you. Security consultants wanting to enhance their Linux security skills will also benefit from this book. Prior knowledge of Linux is mandatory. What You Will Learn ? Use various techniques to prevent intruders from accessing sensitive data ? Prevent intruders from planting malware, and detect whether malware has been planted ? Prevent insiders from accessing data that they aren’t authorized to access ? Do quick checks to see whether a computer is running network services that it doesn’t need to run ? Learn security techniques that are common to all Linux distros, and some that are distro-specific In Detail This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently. By the end of this book, you will be confident in delivering a system that will be much harder to compromise. Style and approach An advanced-level guide filled with real-world examples that will help you secure your Linux system

Create fast and efficient server-side applications using the latest features of Odoo v11 About This Book ? Get the most up-to-date guide on Odoo 11 to create custom and reusable modules ? Interconnect your application with other systems by implementing web APIs ? Understand the mechanisms powering the Odoo framework to build robust enterprises Who This Book Is For If you're a Python developer and want to develop highly efficient business applications with the latest Odoo framework (or if you just want a hands on problem solution book for all your Odoo Development related issues), this book is for you! Some experience with the JavaScript programming language and web development is required to get the most out of this book. What You Will Learn ? Install and manage Odoo environments and instances ? Use models to define your application's data structures ? Add business logic to your applications ? Add automated tests and learn how to debug Odoo apps ? Learn about the access security model and internationalization features ? Customize websites built with Odoo, by writing your own templates and providing new snippets for use in the website builder ? Extend the web client with new widgets and make RPC calls to the server In Detail Odoo is a full-featured open source ERP with a focus on extensibility. The flexibility and sustainability of open source are also a key selling point of Odoo. It is built on a powerful framework for rapid application development, both for back-end applications and front-end websites. Version 11 offers better usability and speed: a new design (as compared to the current Odoo Enterprise version) and a mobile interface. The book starts by covering Odoo installation and administration and Odoo Server deployment. It then delves into the implementation of Odoo modules, the different inheritance models available in Odoo. You will then learn how to define access rules for your data; how to make your application available in different languages; how to expose your data models to end users on the back end and on the front end; and how to create beautiful PDF versions of your data. By the end of the book, you will have a thorough knowledge of Odoo and will be able to build effective applications by applying Odoo development best practices Style and Approach This recipe-based practical guide presents each topic with step-by-step instructions on how you can create fast and efficient server-side applications using the latest features of Odoo v11

Learn to design, implement and secure your IoT infrastructure About This Book ? Build a complete IoT system that is the best fit for your organization ? Learn about different concepts, technologies, and tradeoffs in the IoT architectural stack ? Understand the theory, concepts, and implementation of each element that comprises IoT design—from sensors to the cloud ? Implement best practices to ensure the reliability, scalability, robust communication systems, security, and data analysis in your IoT infrastructure Who This Book Is For This book is for architects, system designers, technologists, and technology managers who want to understand the IoT ecosphere, various technologies, and tradeoffs and develop a 50,000-foot view of IoT architecture. What You Will Learn ? Understand the role and scope of architecting a successful IoT deployment, from sensors to the cloud ? Scan the landscape of IoT technologies that span everything from sensors to the cloud and everything in between ? See the trade-offs in choices of protocols and communications in IoT deployments ? Build a repertoire of skills and the vernacular necessary to work in the IoT space ? Broaden your skills in multiple engineering domains necessary for the IoT architect In Detail The Internet of Things (IoT) is the fastest growing technology market. Industries are embracing IoT technologies to improve operational expenses, product life, and people's well-being. An architectural guide is necessary if you want to traverse the spectrum of technologies needed to build a successful IoT system, whether that's a single device or millions of devices. This book encompasses the entire spectrum of IoT solutions, from sensors to the cloud. We start by examining modern sensor systems and focus on their power and functionality. After that, we dive deep into communication theory, paying close attention to near-range PAN, including the new Bluetooth? 5.0 specification and mesh networks. Then, we explore IP-based communication in LAN and WAN, including 802.11ah, 5G LTE cellular, SigFox, and LoRaWAN. Next, we cover edge routing and gateways and their role in fog computing, as well as the messaging protocols of MQTT and CoAP. With the data now in internet form, you'll get an understanding of cloud and fog architectures, including the OpenFog standards. We wrap up the analytics portion of the book with the application of statistical analysis, complex event processing, and deep learning models. Finally, we conclude by providing a holistic view of the IoT security stack and the anatomical details of IoT exploits while countering them with software defined perimeters and blockchains. Style and approach This hands-on guide combines theory and application to the Internet of Things. This book covers the entire architectural stack of components and engineering domains from sensors to power analysis, communication systems, information theory, networking and routing, data security, protocols, software stacks, cloud mechanics, and data analytics with deep learning.

A perfect guide to speed up the predicting power of machine learning algorithms About This Book ? Design, discover, and create dynamic, efficient features for your machine learning application ? Understand your data in-depth and derive astonishing data insights with the help of this Guide ? Grasp powerful feature-engineering techniques and build machine learning systems Who This Book Is For If you are a data science professional or a machine learning engineer looking to strengthen your predictive analytics model, then this book is a perfect guide for you. Some basic understanding of the machine learning concepts and Python *ing would be enough to get started with this book. What You Will Learn ? Identify and leverage different feature types ? Clean features in data to improve predictive power ? Understand why and how to perform feature selection, and model error analysis ? Leverage domain knowledge to construct new features ? Deliver features based on mathematical insights ? Use machine-learning algorithms to construct features ? Master feature engineering and optimization ? Harness feature engineering for real world applications through a structured case study In Detail Feature engineering is the most important step in creating powerful machine learning systems. This book will take you through the entire feature-engineering journey to make your machine learning much more systematic and effective. You will start with understanding your data—often the success of your ML models depends on how you leverage different feature types, such as continuous, categorical, and more, You will learn when to include a feature, when to omit it, and why, all by understanding error analysis and the acceptability of your models. You will learn to convert a problem statement into useful new features. You will learn to deliver features driven by business needs as well as mathematical insights. You'll also learn how to use machine learning on your machines, automatically learning amazing features for your data. By the end of the book, you will become proficient in Feature Selection, Feature Learning, and Feature Optimization. Style and approach This step-by-step guide with use cases, examples, and illustrations will help you master the concepts of feature engineering. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts later on and will help you implement these techniques in the real world.

Powerful smart applications using deep learning algorithms to dominate numerical computing, deep learning, and functional programming. About This Book ? Explore machine learning techniques with prominent open source Scala libraries such as Spark ML, H2O, MXNet, Zeppelin, and DeepLearning4j ? Solve real-world machine learning problems by delving complex numerical computing with Scala functional programming in a scalable and faster way ? Cover all key aspects such as collection, storing, processing, analyzing, and evaluation required to build and deploy machine models on computing clusters using Scala Play framework. Who This Book Is For If you want to leverage the power of both Scala and Spark to make sense of Big Data, then this book is for you. If you are well versed with machine learning concepts and wants to expand your knowledge by delving into the practical implementation using the power of Scala, then this book is what you need! Strong understanding of Scala Programming language is recommended. Basic familiarity with machine Learning techniques will be more helpful. What You Will Learn ? Apply advanced regression techniques to boost the performance of predictive models ? Use different classification algorithms for business analytics ? Generate trading strategies for Bitcoin and stock trading using ensemble techniques ? Train Deep Neural Networks (DNN) using H2O and Spark ML ? Utilize NLP to build scalable machine learning models ? Learn how to apply reinforcement learning algorithms such as Q-learning for developing ML application ? Learn how to use autoencoders to develop a fraud detection application ? Implement LSTM and CNN models using DeepLearning4j and MXNet In Detail Machine learning has had a huge impact on academia and industry by turning data into actionable information. Scala has seen a steady rise in adoption over the past few years, especially in the fields of data science and analytics. This book is for data scientists, data engineers, and deep learning enthusiasts who have a background in complex numerical computing and want to know more hands-on machine learning application development. If you're well versed in machine learning concepts and want to expand your knowledge by delving into the practical implementation of these concepts using the power of Scala, then this book is what you need! Through 11 end-to-end projects, you will be acquainted with popular machine learning libraries such as Spark ML, H2O, DeepLearning4j, and MXNet. At the end, you will be able to use numerical computing and functional programming to carry out complex numerical tasks to develop, build, and deploy research or commercial projects in a production-ready environment. Style and approach Leverage the power of machine learning and deep learning in different domains, giving best practices and tips from a real world case studies and help you to avoid pitfalls and fallacies towards decision making based on predictive analytics with ML models.

Write code that scales across CPU registers, multi-core, and machine clusters About This Book ? Explore concurrent programming in C++ ? Identify memory management problems ? Use SIMD and STL containers for performance improvement Who This Book Is For If you're a C++ developer looking to improve the speed of your code or simply wanting to take your skills up to the next level, then this book is perfect for you. What You Will Learn ? Find out how to use exciting new tools that will help you improve your code ? Identify bottlenecks to optimize your code ? Develop applications that utilize GPU computation ? Reap the benefits of concurrent programming ? Write code that can protect against application errors using error handling ? Use STL containers and algorithms effciently ? Extend your toolbox with Boost containers ? Achieve effcient memory management by using custom memory allocators In Detail C++ is a highly portable language and can be used to write complex applications and performance-critical code. It has evolved over the last few years to become a modern and expressive language. This book will guide you through optimizing the performance of your C++ apps by allowing them to run faster and consume fewer resources on the device they're running on. The book begins by helping you to identify the bottlenecks in C++. It then moves on to measuring performance, and you'll see how this affects the way you write code. Next, you'll see the importance of data structure optimization and how it can be used efficiently. After that, you'll see which algorithm should be used to achieve faster execution, followed by how to use STL containers. Moving on, you'll learn how to improve memory management in C++. You'll get hands on experience making use of multiple cores to enable more efficient and faster execution. The book ends with a brief overview of utilizing the capabilities of your GPU by using Boost Compute and OpenCL. Style and approach This easy-to-follow guide is full of examples and self-sufficient code snippets that help you with high performance programming with C++. You’ll get your hands dirty with this all-inclusive guide that uncovers hidden performance improvement areas for any C++ code.

Build, scale, and deploy deep neural network models using the star libraries in Python About This Book ? Delve into advanced machine learning and deep learning use cases using Tensorflow and Keras ? Build, deploy, and scale end-to-end deep neural network models in a production environment ? Learn to deploy TensorFlow on mobile, and distributed TensorFlow on GPU, Clusters, and Kubernetes Who This Book Is For This book is for data scientists, machine learning engineers, artificial intelligence engineers, and for all TensorFlow users who wish to upgrade their TensorFlow knowledge and work on various machine learning and deep learning problems. If you are looking for an easy-to-follow guide that underlines the intricacies and complex use cases of machine learning, you will find this book extremely useful. Some basic understanding of TensorFlow is required to get the most out of the book. What You Will Learn ? Master advanced concepts of deep learning such as transfer learning, reinforcement learning, generative models and more, using TensorFlow and Keras ? Perform supervised (classification and regression) and unsupervised (clustering) learning to solve machine learning tasks ? Build end-to-end deep learning (CNN, RNN, and Autoencoders) models with TensorFlow ? Scale and deploy production models with distributed and high-performance computing on GPU and clusters ? Build TensorFlow models to work with multilayer perceptrons using Keras, TFLearn, and R ? Learn the functionalities of smart apps by building and deploying TensorFlow models on iOS and Android devices ? Supercharge TensorFlow with distributed training and deployment on Kubernetes and TensorFlow Clusters In Detail TensorFlow is the most popular numerical computation library built from the ground up for distributed, cloud, and mobile environments. TensorFlow represents the data as tensors and the computation as graphs. This book is a comprehensive guide that lets you explore the advanced features of TensorFlow 1.x. Gain insight into TensorFlow Core, Keras, TF Estimators, TFLearn, TF Slim, Pretty Tensor, and Sonnet. Leverage the power of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Throughout the book, you will obtain hands-on experience with varied datasets, such as MNIST, CIFAR-10, PTB, text8, and COCO-Images. You will learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF Clusters, deploy production models with TensorFlow Serving, and build and deploy TensorFlow models for mobile and embedded devices on Android and iOS platforms. You will see how to call TensorFlow and Keras API within the R statistical software, and learn the required techniques for debugging when the TensorFlow API-based code does not work as expected. The book helps you obtain in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problems. By the end of this guide, you will have mastered the offerings of TensorFlow and Keras, and gained the skills you need to build smarter, faster, and efficient machine learning and deep learning systems. Style and approach Step-by-step comprehensive guide filled with advanced, real-world examples to help you master Tensorflow 1.x

Learn how to model and train advanced neural networks to implement a variety of Computer Vision tasks About This Book ? Train different kinds of deep learning model from scratch to solve specific problems in Computer Vision ? Combine the power of Python, Keras, and TensorFlow to build deep learning models for object detection, image classification, similarity learning, image captioning, and more ? Includes tips on optimizing and improving the performance of your models under various constraints Who This Book Is For This book is targeted at data scientists and Computer Vision practitioners who wish to apply the concepts of Deep Learning to overcome any problem related to Computer Vision. A basic knowledge of programming in Python—and some understanding of machine learning concepts—is required to get the best out of this book. What You Will Learn ? Set up an environment for deep learning with Python, TensorFlow, and Keras ? Define and train a model for image and video classification ? Use features from a pre-trained Convolutional Neural Network model for image retrieval ? Understand and implement object detection using the real-world Pedestrian Detection scenario ? Learn about various problems in image captioning and how to overcome them by training images and text together ? Implement similarity matching and train a model for face recognition ? Understand the concept of generative models and use them for image generation ? Deploy your deep learning models and optimize them for high performance In Detail Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision. Computer Vision is the science of understanding and manipulating images, and finds enormous applications in the areas of robotics, automation, and so on. This book will also show you, with practical examples, how to develop Computer Vision applications by leveraging the power of deep learning. In this book, you will learn different techniques related to object classification, object detection, image segmentation, captioning, image generation, face analysis, and more. You will also explore their applications using popular Python libraries such as TensorFlow and Keras. This book will help you master state-of-the-art, deep learning algorithms and their implementation. Style and approach This book will teach advanced techniques for Computer Vision, applying the deep learning model in reference to various datasets.

Design, build and test RESTful web services with the Django framework and Python About This Book ? Create efficient real-world RESTful web services with the latest Django framework ? Authenticate, secure, and integrate third-party packages efficiently in your Web Services ? Leverage the power of Python for faster Web Service development Who This Book Is For This book is for Python developers who want to create RESTful web services with Django; you need to have a basic working knowledge of Django but no previous experience with RESTful web services is required. What You Will Learn ? The best way to build a RESTful Web Service or API with Django and the Django REST Framework ? Develop complex RESTful APIs from scratch with Django and the Django REST Framework ? Work with either SQL or NoSQL data sources ? Design RESTful Web Services based on application requirements ? Use third-party packages and extensions to perform common tasks ? Create automated tests for RESTful web services ? Debug, test, and profile RESTful web services with Django and the Django REST Framework In Detail Django is a Python web framework that makes the web development process very easy. It reduces the amount of trivial code, which simplifies the creation of web applications and results in faster development. It is very powerful and a great choice for creating RESTful web services. If you are a Python developer and want to efficiently create RESTful web services with Django for your apps, then this is the right book for you. The book starts off by showing you how to install and configure the environment, required software, and tools to create RESTful web services with Django and the Django REST framework. We then move on to working with advanced serialization and migrations to interact with SQLite and non-SQL data sources. We will use the features included in the Django REST framework to improve our simple web service. Further, we will create API views to process diverse HTTP requests on objects, go through relationships and hyperlinked API management, and then discover the necessary steps to include security and permissions related to data models and APIs. We will also apply throttling rules and run tests to check that versioning works as expected. Next we will run automated tests to improve code coverage. By the end of the book, you will be able to build RESTful web services with Django." Style and approach The book takes a straightforward approach, giving you the techniques and best use cases to build great web services with Django and Python

Design and administer enterprise-grade MySQL 8 solutions About This Book ? Store, retrieve, and manipulate your data using the latest MySQL 8 features ? Practical recipes on effective administration in MySQL, with a focus on security, performance tuning, troubleshooting, and more ? Contains tips, tricks, and best practices for designing, developing, and administering your MySQL 8 database solution without any hassle Who This Book Is For If you are a MySQL developer or administrator looking for quick, handy solutions to solve the most common and not-so-common problems in MySQL, this book is for you. MySQL DBAs looking to get up-to-speed with the latest MySQL 8 development and administration features will also find this book very useful. Prior knowledge of Linux and RDBMS is desirable. What You Will Learn ? Install and configure your MySQL 8 instance without any hassle ? Get to grips with new features of MySQL 8 like CTE, Window functions and many more ? Perform backup tasks, recover data and set up various replication topologies for your database ? Maximize performance by using new features of MySQL 8 like descending indexes, controlling query optimizer and resource groups ? Learn how to use general table space to suit the SaaS or multi-tenant applications ? Analyze slow queries using performance schema, sys schema and third party tools ? Manage and monitor your MySQL instance and implement efficient performance-tuning tasks In Detail MySQL is one of the most popular and widely used relational databases in the World today. The recently released MySQL 8 version promises to be better and more efficient than ever before. This book contains everything you need to know to be the go-to person in your organization when it comes to MySQL. Starting with a quick installation and configuration of your MySQL instance, the book quickly jumps into the querying aspects of MySQL. It shows you the newest improvements in MySQL 8 and gives you hands-on experience in managing high-transaction and real-time datasets. If you've already worked with MySQL before and are looking to migrate your application to MySQL 8, this book will also show you how to do that. The book also contains recipes on efficient MySQL administration, with tips on effective user management, data recovery, security, database monitoring, performance tuning, troubleshooting, and more. With quick solutions to common and not-so-common problems you might encounter while working with MySQL 8, the book contains practical tips and tricks to give you the edge over others in designing, developing, and administering your database effectively. Style and approach This book takes a recipe-based approach to tackling the pain points of SQL developers. It is a comprehensive book full of solutions to common problems faced by SQL administrators and developers alike.

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

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

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

Unleash the power of MERN stack by building diverse web applications using React, Node.js, Express, and MongoDB About This Book ? Create dynamic web applications with the MERN stack ? Leverage the power of React in building interactive and complex user interfaces ? Unlock the potential of Node, Express, and MongoDB to build modern full-stack applications Who This Book Is For Full-Stack React Web Development Projects is for JavaScript developers who have some experience with React, but no previous experience with full-stack development involving Node, Express, and MongoDB, and who want practical guidelines to start building different types of real-world web applications with this stack. What You Will Learn ? Set up your development environment and develop a MERN application ? Implement user authentication and authorization using JSON Web Tokens ? Build a social media application by extending the basic MERN application ? Create an online marketplace application with shopping cart and Stripe payments ? Develop a media streaming application using MongoDB GridFS ? Implement server-side rendering with data to improve SEO ? Set up and use React 360 to develop user interfaces with VR capabilities ? Learn industry best practices to make MERN stack applications reliable and scalable In Detail The benefits of using a full JavaScript stack for web development are undeniable, especially when robust and widely adopted technologies such as React, Node, and Express and are available. Combining the power of React with industry-tested, server-side technologies, such as Node, Express, and MongoDB, creates a diverse array of possibilities when developing real-world web applications. This book guides you through preparing the development environment for MERN stack-based web development, to creating a basic skeleton application and extending it to build four different web applications. These applications include a social media, an online marketplace, a media streaming, and a web-based game application with virtual reality features. While learning to set up the stack and developing a diverse range of applications with this book, you will grasp the inner workings of the MERN stack, extend its capabilities for complex features, and gain actionable knowledge of how to prepare MERN-based applications to meet the growing demands of real-world web applications. Style and approach This book provides practical guidelines on setting up and building MERN stack based applications, while providing further explanations on key concepts and implementations.

Get up-to-date with the finer points of Ubuntu Server using this comprehensive guide About This Book ? A practical easy-to-understand book that will teach you how to deploy, maintain and troubleshoot Ubuntu Server ? Get well-versed with newly-added features in Ubuntu 18.04. ? Learn to manage cutting-edge technologies such as virtualization, containers, Nextcloud and more Who This Book Is For This book is intended for readers with intermediate or advanced-beginner skills with Linux, who would like to learn all about setting up servers with Ubuntu Server. This book assumes that the reader knows the basics of Linux, such as editing configuration files and running basic commands. What You Will Learn ? Manage users, groups, and permissions ? Encrypt and decrypt disks with Linux Unified Key Setup (LUKS) ? Set up SSH for remote access, and connect it to other nodes ? Add, remove, and search for packages ? Use NFS and Samba to share directories with other users ? Get to know techniques for managing Apache and MariaDB ? Explore best practices and troubleshooting techniques ? Get familiar with scripting ? Automate server deployments with Ansible In Detail Ubuntu Server has taken the data centers by storm. Whether you're deploying Ubuntu for a large-scale project or for a small office, it is a stable, customizable, and powerful Linux distribution that leads the way with innovative and cutting-edge features. For both simple and complex server deployments, Ubuntu's flexible nature can be easily adapted to meet to the needs of your organization. With this book as your guide, you will learn all about Ubuntu Server, from initial deployment to creating production-ready resources for your network. The book begins with the concept of user management, group management, and filesystem permissions. Continuing into managing storage volumes, you will learn how to format storage devices, utilize logical volume management, and monitor disk usage. Later, you will learn how to virtualize hosts and applications, which will cover setting up KVM/QEMU, as well as containerization with both Docker and LXD. As the book continues, you will learn how to automate configuration with Ansible, as well as take a look at writing scripts. Lastly, you will explore best practices and troubleshooting techniques when working with Ubuntu Server that are applicable to real-world scenarios. By the end of the book, you will be an expert Ubuntu Server administrator who is well-versed in its advanced concepts. Style and approach This book is an advanced guide that will show readers how to administer, manage, and deploy Ubuntu server and will also provide expert-level knowledge on advanced security and backup techniques.

A complete guide on course development and delivery using Moodle 3.x About This Book ? Get the best out of the latest Moodle 3 framework to ensure successful learning ? Gain experience in creating different kinds of courses ? Create your first Moodle VR app using the Moodle VR toolset Who This Book Is For This book is for anyone who wants to get the best out of Moodle. As a beginner, this is a thorough guide for you to understand how the software works, with great ideas for getting off to a good start with your first course. Some experience of working with e-learning systems will be beneficial. Experienced Moodle users will find powerful insights into developing successful and educational courses. What You Will Learn ? Know what Moodle does and how it supports your teaching strategies ? Install Moodle on your computer and navigate your way around it ? Understand all of Moodle's learning features ? Monitor how learners interact with your site using site statistics ? Add multimedia content to your site ? Allow students to enroll themselves or invite other students to join a course In Detail Moodle is a learning platform or Course Management System (CMS) that is easy to install and use, but the real challenge is in developing a learning process that leverages its power and maps the learning objectives to content and assessments for an integrated and effective course. Moodle 3 E-Learning Course Development guides you through meeting that challenge in a practical way. This latest edition will show you how to add static learning material, assessments, and social features such as forum-based instructional strategy, a chat module, and forums to your courses so that students reach their learning potential. Whether you want to support traditional class teaching or lecturing, or provide complete online and distance e-learning courses, this book will prove to be a powerful resource throughout your use of Moodle. You’ll learn how to create and integrate third-party plugins and widgets in your Moodle app, implement site permissions and user accounts, and ensure the security of content and test papers. Further on, you’ll implement PHP scripts that will help you create customized UIs for your app. You’ll also understand how to create your first Moodle VR e-learning app using the latest VR learning experience that Moodle 3 has to offer. By the end of this book, you will have explored the decisions, design considerations, and thought processes that go into developing a successful course. Style and approach Packed with clear step-by-step instructions, plenty of screenshots, and thorough explanations, this book guides you through the many features and options that you have to choose from when using Moodle 3.

Learn to design and develop safe and reliable embedded systems About This Book ? Identify and overcome challenges in embedded environments ? Understand the steps required to increase the security of IoT solutions ? Build safety-critical and memory-safe parallel and distributed embedded systems Who This Book Is For If you’re a software developer or designer wanting to learn about embedded programming, this is the book for you. You’ll also find this book useful if you’re a less experienced embedded programmer willing to expand your knowledge. What You Will Learn ? Participate in the design and definition phase of an embedded product ? Get to grips with writing code for ARM Cortex-M microcontrollers ? Build an embedded development lab and optimize the workflow ? Write memory-safe code ? Understand the architecture behind the communication interfaces ? Understand the design and development patterns for connected and distributed devices in the IoT ? Master multitask parallel execution patterns and real-time operating systems In Detail Embedded systems are self-contained devices with a dedicated purpose. We come across a variety of fields of applications for embedded systems in industries such as automotive, telecommunications, healthcare and consumer electronics, just to name a few. Embedded Systems Architecture begins with a bird's eye view of embedded development and how it differs from the other systems that you may be familiar with. You will first be guided to set up an optimal development environment, then move on to software tools and methodologies to improve the work flow. You will explore the boot-up mechanisms and the memory management strategies typical of a real-time embedded system. Through the analysis of the programming interface of the reference microcontroller, you'll look at the implementation of the features and the device drivers. Next, you'll learn about the techniques used to reduce power consumption. Then you will be introduced to the technologies, protocols and security aspects related to integrating the system into IoT solutions. By the end of the book, you will have explored various aspects of embedded architecture, including task synchronization in a multi-threading environment, and the safety models adopted by modern real-time operating systems. Style and approach Software developers and designers with experience in different fields, and who want to learn about embedded programming, will benefit from this book. Junior and less experienced embedded programmers willing to expand their knowledge in the field will also find it useful.