Python: Advanced Guide to Programming Code with Python

Sorting Algorithms In Computer Programming: Volume 1

Using Speech Recognition Software & Equipment to Write Books

JavaScript: Advanced Guide to Programming Code with JavaScript

JavaScript: Best Practices to Programming Code with JavaScript

Delve into the world of Kotlin and learn to build powerful Android and web applications Key Features * Learn the fundamentals of Kotlin to write high-quality code * Test and debug your applications with the different unit testing frameworks in Kotlin * Explore Kotlin's interesting features such as null safety, reflection, and annotations Book Description Kotlin is a general-purpose programming language used for developing cross-platform applications. Complete with a comprehensive introduction and projects covering the full set of Kotlin programming features, this book will take you through the fundamentals of Kotlin and get you up to speed in no time. Learn Kotlin Programming covers the installation, tools, and how to write basic programs in Kotlin. You'll learn how to implement object-oriented programming in Kotlin and easily reuse your program or parts of it. The book explains DSL construction, serialization, null safety aspects, and type parameterization to help you build robust apps. You'll learn how to destructure expressions and write your own. You'll then get to grips with building scalable apps by exploring advanced topics such as testing, concurrency, microservices, coroutines, and Kotlin DSL builders. Furthermore, you'll be introduced to the kotlinx.serialization framework, which is used to persist objects in JSON, Protobuf, and other formats. By the end of this book, you'll be well versed with all the new features in Kotlin and will be able to build robust applications skillfully. What you will learn * Explore the latest Kotlin features in order to write structured and readable object-oriented code * Get to grips with using lambdas and higher-order functions * Write unit tests and integrate Kotlin with Java code * Create real-world apps in Kotlin in the microservices style * Use Kotlin extensions with the Java collections library * Uncover destructuring expressions and find out how to write your own * Understand how Java-nullable code can be integrated with Kotlin features Who this book is for If you’re a beginner or intermediate programmer who wants to learn Kotlin to build applications, this book is for you. You’ll also find this book useful if you’re a Java developer interested in switching to Kotlin.

Take your SAP ABAP skills to the next level by mastering ABAP programming techniques with the help of real-world examples Key Features * Become adept at building interfaces and explore ABAP tools and techniques * Discover the modern functionalities available in the latest version of ABAP * Learn the process of creating stunning HTML5 applications using SAPUI5 Book Description Advanced Business Application Programming (ABAP) is an established and complex programming language in the IT industry. This book is designed to help you use the latest ABAP techniques and apply legacy constructions using practical examples. You'll start with a quick refresher on language and database concepts, followed by agile techniques for adding custom code to a modern ABAP system. After this, you will get up to speed with the complete ABAP toolset for importing data to and from different environments. Next, you'll learn how to print forms and work with the different ABAP tools for Extensible Markup Language (XML) manipulation. While covering further chapters, you'll gain insights into building stunning UI5 interfaces, in addition to learning how to develop simple apps using the Business Object Processing Framework (BOPF). You will also pick up the technique of handling exceptions and performing testing in ABAP. In the concluding chapters, you can look forward to grasping various techniques for optimizing the performance of programs using a variety of performance analysis tools. By the end of this book, you will have the expertise you need to confidently build maintainable programs in Systems, Applications, and Products (SAP). What you will learn * Create stable and error-free ABAP programs * Leverage new ABAP concepts including object-oriented programming(OOP) and Model-View-Controller (MVC) * Learn to add custom code to your existing SAP program * Speed up your ABAP programs by spotting bottlenecks * Understand techniques such as performance tuning and optimization * Develop modern and beautiful user interfaces (UIs) in an ABAP environment * Build multiple classes with any nesting level Who this book is for This book is for developers who want to learn and use ABAP skills to become an industry expert. Familiarity with object-oriented programming concepts is expected.

Manage Microsoft Azure cloud services that span storage, security, networking, and compute cloud capabilities and ace the AZ-103 Exam Key Features * Master features and concepts pertaining to Azure's Administration services * Gain a deep understanding of various Azure services related to infrastructure, applications, and environments * Gauge yourself by giving mock tests with up-to-date exam questions Book Description Microsoft Azure Administrator – Exam Guide AZ-103 will cover all the exam objectives that will help you earn Microsoft Azure Administrator certification. Whether you want to clear AZ-103 exam or want hands-on experience in administering Azure, this study guide will help you achieve your objective. It covers the latest features and capabilities around configuring, managing, and securing Azure resources. Following Microsoft's AZ-103 exam syllabus, this guide is divided into five modules. The first module talks about how to manage Azure subscriptions and resources. You will be able to configure Azure subscription policies at Azure subscription level and learn how to use Azure policies for resource groups. Later, the book covers techniques related to implementing and managing storage in Azure. You will be able to create and configure backup policies and perform restore operations. The next module will guide you to create, configure, and deploy virtual machines for Windows and Linux. In the last two modules, you will learn about configuring and managing virtual networks and managing identities. The book concludes with effective mock tests along with answers so that you can confidently crack this exam. By the end of this book, you will acquire the skills needed to pass Exam AZ-103. What you will learn * Configure Azure subscription policies and manage resource groups * Monitor activity log by using Log Analytics * Modify and deploy Azure Resource Manager (ARM) templates * Protect your data with Azure Site Recovery * Learn how to manage identities in Azure * Monitor and troubleshoot virtual network connectivity * Manage Azure Active Directory Connect, password sync, and password writeback Who this book is for This book is for Azure administrators, systems administrators or anyone preparing for AZ 103 exam and wants to master Azure's various administration features. Readers should have proficiency in working with PowerShell, CLI and other day-to-day Azure administration tasks.

Build Prometheus ecosystems with metric-centric visualization, alerting, and querying Key Features * Integrate Prometheus with Alertmanager and Grafana for building a complete monitoring system * Explore PromQL, Prometheus' functional query language, with easy-to-follow examples * Learn how to deploy Prometheus components using Kubernetes and traditional instances Book Description Prometheus is an open source monitoring system. It provides a modern time series database, a robust query language, several metric visualization possibilities, and a reliable alerting solution for traditional and cloud-native infrastructure. This book covers the fundamental concepts of monitoring and explores Prometheus architecture, its data model, and how metric aggregation works. Multiple test environments are included to help explore different configuration scenarios, such as the use of various exporters and integrations. You’ll delve into PromQL, supported by several examples, and then apply that knowledge to alerting and recording rules, as well as how to test them. After that, alert routing with Alertmanager and creating visualizations with Grafana is thoroughly covered. In addition, this book covers several service discovery mechanisms and even provides an example of how to create your own. Finally, you’ll learn about Prometheus federation, cross-sharding aggregation, and also long-term storage with the help of Thanos. By the end of this book, you’ll be able to implement and scale Prometheus as a full monitoring system on-premises, in cloud environments, in standalone instances, or using container orchestration with Kubernetes. What you will learn * Grasp monitoring fundamentals and implement them using Prometheus * Discover how to extract metrics from common infrastructure services * Find out how to take full advantage of PromQL * Design a highly available, resilient, and scalable Prometheus stack * Explore the power of Kubernetes Prometheus Operator * Understand concepts such as federation and cross-shard aggregation * Unlock seamless global views and long-term retention in cloud-native apps with Thanos Who this book is for If you’re a software developer, cloud administrator, site reliability engineer, DevOps enthusiast or system admin looking to set up a fail-safe monitoring and alerting system for sustaining infrastructure security and performance, this book is for you. Basic networking and infrastructure monitoring knowledge will help you understand the concepts covered in this book.

Explore the aspects of financial modeling with the help of clear and easy-to-follow instructions and a variety of Excel features, functions, and productivity tips Key Features * A non data professionals guide to exploring Excel's financial functions and pivot tables * Learn to prepare various models for income and cash flow statements, and balance sheets * Learn to perform valuations and identify growth drivers with real-world case studies Book Description Financial modeling is a core skill required by anyone who wants to build a career in finance. Hands-On Financial Modeling with Microsoft Excel 2019 examines various definitions and relates them to the key features of financial modeling with the help of Excel. This book will help you understand financial modeling concepts using Excel, and provides you with an overview of the steps you should follow to build an integrated financial model. You will explore the design principles, functions, and techniques of building models in a practical manner. Starting with the key concepts of Excel, such as formulas and functions, you will learn about referencing frameworks and other advanced components of Excel for building financial models. Later chapters will help you understand your financial projects, build assumptions, and analyze historical data to develop data-driven models and functional growth drivers. The book takes an intuitive approach to model testing, along with best practices and practical use cases. By the end of this book, you will have examined the data from various use cases, and you will have the skills you need to build financial models to extract the information required to make informed business decisions. What you will learn * Identify the growth drivers derived from processing historical data in Excel * Use discounted cash flow (DCF) for efficient investment analysis * Build a financial model by projecting balance sheets, profit, and loss * Apply a Monte Carlo simulation to derive key assumptions for your financial model * Prepare detailed asset and debt schedule models in Excel * Discover the latest and advanced features of Excel 2019 * Calculate profitability ratios using various profit parameters Who this book is for This book is for data professionals, analysts, traders, business owners, and students, who want to implement and develop a high in-demand skill of financial modeling in their finance, analysis, trading, and valuation work. This book will also help individuals that have and don't have any experience in data and stats, to get started with building financial models. The book assumes working knowledge with Excel.

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.

Leverage the power of Java and deep learning to build production-grade Computer Vision applications Key Features * Build real-world Computer Vision applications using the power of neural networks * Implement image classification, object detection, and face recognition * Know best practices on effectively building and deploying deep learning models in Java Book Description Although machine learning is an exciting world to explore, you may feel confused by all of its theoretical aspects. As a Java developer, you will be used to telling the computer exactly what to do, instead of being shown how data is generated; this causes many developers to struggle to adapt to machine learning. The goal of this book is to walk you through the process of efficiently training machine learning and deep learning models for Computer Vision using the most up-to-date techniques. The book is designed to familiarize you with neural networks, enabling you to train them efficiently, customize existing state-of-the-art architectures, build real-world Java applications, and get great results in a short space of time. You will build real-world Computer Vision applications, ranging from a simple Java handwritten digit recognition model to real-time Java autonomous car driving systems and face recognition models. By the end of this book, you will have mastered the best practices and modern techniques needed to build advanced Computer Vision Java applications and achieve production-grade accuracy. What you will learn * Discover neural networks and their applications in Computer Vision * Explore the popular Java frameworks and libraries for deep learning * Build deep neural networks in Java * Implement an end-to-end image classification application in Java * Perform real-time video object detection using deep learning * Enhance performance and deploy applications for production Who this book is for This book is for data scientists, machine learning developers and deep learning practitioners with Java knowledge who want to implement machine learning and deep neural networks in the computer vision domain. You will need to have a basic knowledge of Java programming.

Discover Golang's GUI libraries such as Go-GTK (GIMP Toolkit) and Go-Qt and build beautiful, performant, and responsive graphical applications Key Features * Conceptualize and build state-of-art GUI applications with Golang (Go) * Tackle the complexity of varying GUI application sizes with a structured and scalable approach * Get hands-on experience of GUI development with Shiny, and labs/ui, Fyne, and Walk Book Description Go is often compared to C++ when it comes to low-level programming and implementations that require faster processing, such as Graphical User Interfaces (GUIs). In fact, many claim that Go is superior to C++ in terms of its concurrency and ease of use. Most graphical application toolkits, though, are still written using C or C++, and so they don't enjoy the benefits of using a modern programming language such as Go. This guide to programming GUIs with Go 1.11 explores the various toolkits available, including UI, Walk, Shiny, and Fyne. The book compares the vision behind each project to help you pick the right approach for your project. Each framework is described in detail, outlining how you can build performant applications that users will love. To aid you further in creating applications using these emerging technologies, you'll be able to easily refer to code samples and screenshots featured in the book. In addition to toolkit-specific discussions, you'll cover more complex topics, such as how to structure growing graphical applications, and how cross-platform applications can integrate with each desktop operating system to create a seamless user experience. By delving into techniques and best practices for organizing and scaling Go-based graphical applications, you'll also glimpse Go's impressive concurrency system. In the concluding chapters, you'll discover how to distribute to the main desktop marketplaces and distribution channels. By the end of this book, you'll be a confident GUI developer who can use the Go language to boost the performance of your applications. What you will learn * Understand the benefits and complexities of building native graphical applications * Gain insights into how Go makes cross-platform graphical application development simple * Build platform-native GUI applications using andlabs/ui * Develop graphical Windows applications using Walk * Create multiplatform GUI applications using Shiny, Nuklear, and Fyne * Use Go wrappers for GTK and Qt for GUI application development * Streamline your requirements to pick the correct toolkit strategy Who this book is for This book is designed for Go developers who are interested in building native graphical applications for desktop computers and beyond. Some knowledge of building applications using Go is useful, but not essential. Experience in developing GUIs is not required as the book explores the benefits and challenges they pose. This book will also be beneficial for GUI application developers who are interested in trying Go.

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features *A step-by-step guide to conduct Bayesian data analyses using PyMC3 and ArviZ *A modern, practical and computational approach to Bayesian statistical modeling *A tutorial for Bayesian analysis and best practices with the help of sample problems and practice exercises. Book Description The second edition of Bayesian Analysis with Python is an introduction to the main concepts of applied Bayesian inference and its practical implementation in Python using PyMC3, a state-of-the-art probabilistic programming library, and ArviZ, a new library for exploratory analysis of Bayesian models. The main concepts of Bayesian statistics are covered using a practical and computational approach. Synthetic and real data sets are used to introduce several types of models, such as generalized linear models for regression and classification, mixture models, hierarchical models, and Gaussian processes, among others. By the end of the book, you will have a working knowledge of probabilistic modeling and you will be able to design and implement Bayesian models for your own data science problems. After reading the book you will be better prepared to delve into more advanced material or specialized statistical modeling if you need to. What you will learn *Build probabilistic models using the Python library PyMC3 *Analyze probabilistic models with the help of ArviZ *Acquire the skills required to sanity check models and modify them if necessary *Understand the advantages and caveats of hierarchical models *Find out how different models can be used to answer different data analysis questions *Compare models and choose between alternative ones *Discover how different models are unified from a probabilistic perspective *Think probabilistically and benefit from the flexibility of the Bayesian framework Who this book is for If you are a student, data scientist, researcher, or a developer looking to get started with Bayesian data analysis and probabilistic programming, this book is for you. The book is introductory so no previous statistical knowledge is required, although some experience in using Python and NumPy is expected.

Your one stop guide to automating infrastructure security using DevOps and DevSecOps Key Features * Secure and automate techniques to protect web, mobile or cloud services * Automate secure code inspection in C++, Java, Python, and JavaScript * Integrate security testing with automation frameworks like fuzz, BDD, Selenium and Robot Framework Book Description Security automation is the automatic handling of software security assessments tasks. This book helps you to build your security automation framework to scan for vulnerabilities without human intervention. This book will teach you to adopt security automation techniques to continuously improve your entire software development and security testing. You will learn to use open source tools and techniques to integrate security testing tools directly into your CI/CD framework. With this book, you will see how to implement security inspection at every layer, such as secure code inspection, fuzz testing, Rest API, privacy, infrastructure security, and web UI testing. With the help of practical examples, this book will teach you to implement the combination of automation and Security in DevOps. You will learn about the integration of security testing results for an overall security status for projects. By the end of this book, you will be confident implementing automation security in all layers of your software development stages and will be able to build your own in-house security automation platform throughout your mobile and cloud releases. What you will learn * Automate secure code inspection with open source tools and effective secure code scanning suggestions * Apply security testing tools and automation frameworks to identify security vulnerabilities in web, mobile and cloud services * Integrate security testing tools such as OWASP ZAP, NMAP, SSLyze, SQLMap, and OpenSCAP * Implement automation testing techniques with Selenium, JMeter, Robot Framework, Gauntlt, BDD, DDT, and Python unittest * Execute security testing of a Rest API Implement web application security with open source tools and script templates for CI/CD integration * Integrate various types of security testing tool results from a single project into one dashboard Who this book is for The book is for software developers, architects, testers and QA engineers who are looking to leverage automated security testing techniques.

Discover the latest features of Spring framework by building robust, fast, and reactive web applications Key Features * Take advantage of all the features of Spring 5.0 with third party tools to build a robust back end * Secure Spring based web application using Spring Security framework with LDAP and OAuth protocol * Develop robust and scalable microservice based applications on Spring Cloud, using Spring Boot Book Description Spring makes it easy to create RESTful applications, merge with social services, communicate with modern databases, secure your system, and make your code modular and easy to test. With the arrival of Spring Boot, developers can really focus on the code and deliver great value, with minimal contour. This book will show you how to build various projects in Spring 5.0, using its features and third party tools. We'll start by creating a web application using Spring MVC, Spring Data, the World Bank API for some statistics on different countries, and MySQL database. Moving ahead, you'll build a RESTful web services application using Spring WebFlux framework. You'll be then taken through creating a Spring Boot-based simple blog management system, which uses Elasticsearch as the data store. Then, you'll use Spring Security with the LDAP libraries for authenticating users and create a central authentication and authorization server using OAuth 2 protocol. Further, you'll understand how to create Spring Boot-based monolithic application using JHipster. Toward the end, we'll create an online book store with microservice architecture using Spring Cloud and Net?ix OSS components, and a task management system using Spring and Kotlin. By the end of the book, you'll be able to create coherent and ?exible real-time web applications using Spring Framework. What you will learn * Build Spring based application using Bootstrap template and JQuery * Understand the Spring WebFlux framework and how it uses Reactor library * Interact with Elasticsearch for indexing, querying, and aggregating data * Create a simple monolithic application using JHipster * Use Spring Security and Spring Security LDAP and OAuth libraries for Authentication * Develop a microservice-based application with Spring Cloud and Netflix * Work on Spring Framework with Kotlin Who this book is for This book is for competent Spring developers who wish to understand how to develop complex yet flexible applications with Spring. You must have a good knowledge of Java programming and be familiar with the basics of Spring.

Understand how to apply distributed tracing to microservices-based architectures Key Features * A thorough conceptual introduction to distributed tracing * An exploration of the most important open standards in the space * A how-to guide for code instrumentation and operating a tracing infrastructure Book Description Mastering Distributed Tracing will equip you to operate and enhance your own tracing infrastructure. Through practical exercises and code examples, you will learn how end-to-end tracing can be used as a powerful application performance management and comprehension tool. The rise of Internet-scale companies, like Google and Amazon, ushered in a new era of distributed systems operating on thousands of nodes across multiple data centers. Microservices increased that complexity, often exponentially. It is harder to debug these systems, track down failures, detect bottlenecks, or even simply understand what is going on. Distributed tracing focuses on solving these problems for complex distributed systems. Today, tracing standards have developed and we have much faster systems, making instrumentation less intrusive and data more valuable. Yuri Shkuro, the creator of Jaeger, a popular open-source distributed tracing system, delivers end-to-end coverage of the field in Mastering Distributed Tracing. Review the history and theoretical foundations of tracing; solve the data gathering problem through code instrumentation, with open standards like OpenTracing, W3C Trace Context, and OpenCensus; and discuss the benefits and applications of a distributed tracing infrastructure for understanding, and profiling, complex systems. What you will learn * How to get started with using a distributed tracing system * How to get the most value out of end-to-end tracing * Learn about open standards in the space * Learn about code instrumentation and operating a tracing infrastructure * Learn where distributed tracing fits into microservices as a core function Who this book is for Any developer interested in testing large systems will find this book very revealing and in places, surprising. Every microservice architect and developer should have an insight into distributed tracing, and the book will help them on their way. System administrators with some development skills will also benefit. No particular programming language skills are required, although an ability to read Java, while non-essential, will help with the core chapters.

A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key Features * Use Microsoft's product Excel to build advanced forecasting models using varied examples * Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more * Derive data-driven techniques using Excel plugins and APIs without much code required Book Description We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learn * Use Excel to preview and cleanse datasets * Understand correlations between variables and optimize the input to machine learning models * Use and evaluate different machine learning models from Excel * Understand the use of different visualizations * Learn the basic concepts and calculations to understand how artificial neural networks work * Learn how to connect Excel to the Microsoft Azure cloud * Get beyond proof of concepts and build fully functional data analysis flows Who this book is for This book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

Use Ansible to configure your systems, deploy software, and orchestrate advanced IT tasks Key Features * Get familiar with the fundamentals of Ansible 2.7 * Understand how to use Ansible Tower to scale your IT automation * Gain insights into how to develop and test Ansible playbooks Book Description Ansible is an open source automation platform that assists organizations with tasks such as application deployment, orchestration, and task automation. With the release of Ansible 2.7, even complex tasks can be handled much more easily than before. Learning Ansible 2.7 will help you take your first steps toward understanding the fundamentals and practical aspects of Ansible by introducing you to topics such as playbooks, modules, and the installation of Linux, Berkeley Software Distribution (BSD), and Windows support. In addition to this, you will focus on various testing strategies, deployment, and orchestration to build on your knowledge. The book will then help you get accustomed to features including cleaner architecture, task blocks, and playbook parsing, which can help you to streamline automation processes. Next, you will learn how to integrate Ansible with cloud platforms such as Amazon Web Services (AWS) before gaining insights into the enterprise versions of Ansible, Ansible Tower and Ansible Galaxy. This will help you to use Ansible to interact with different operating systems and improve your working efficiency. By the end of this book, you will be equipped with the Ansible skills you need to automate complex tasks for your organization. What you will learn * Create a web server using Ansible * Write a custom module and test it * Deploy playbooks in the production environment * Troubleshoot networks using Ansible * Use Ansible Galaxy and Ansible Tower during deployment * Deploy an application with Ansible on AWS, Azure and DigitalOcean Who this book is for This beginner-level book is for system administrators who want to automate their organization's infrastructure using Ansible 2.7. No prior knowledge of Ansible is required

Discover a project-based approach to mastering machine learning concepts by applying them to everyday problems using libraries such as scikit-learn, TensorFlow, and Keras Key Features * Get to grips with Python's machine learning libraries including scikit-learn, TensorFlow, and Keras * Implement advanced concepts and popular machine learning algorithms in real-world projects * Build analytics, computer vision, and neural network projects Book Description Machine learning is transforming the way we understand and interact with the world around us. This book is the perfect guide for you to put your knowledge and skills into practice and use the Python ecosystem to cover key domains in machine learning. This second edition covers a range of libraries from the Python ecosystem, including TensorFlow and Keras, to help you implement real-world machine learning projects. The book begins by giving you an overview of machine learning with Python. With the help of complex datasets and optimized techniques, you’ll go on to understand how to apply advanced concepts and popular machine learning algorithms to real-world projects. Next, you’ll cover projects from domains such as predictive analytics to analyze the stock market and recommendation systems for GitHub repositories. In addition to this, you’ll also work on projects from the NLP domain to create a custom news feed using frameworks such as scikit-learn, TensorFlow, and Keras. Following this, you’ll learn how to build an advanced chatbot, and scale things up using PySpark. In the concluding chapters, you can look forward to exciting insights into deep learning and you'll even create an application using computer vision and neural networks. By the end of this book, you’ll be able to analyze data seamlessly and make a powerful impact through your projects. What you will learn * Understand the Python data science stack and commonly used algorithms * Build a model to forecast the performance of an Initial Public Offering (IPO) over an initial discrete trading window * Understand NLP concepts by creating a custom news feed * Create applications that will recommend GitHub repositories based on ones you’ve starred, watched, or forked * Gain the skills to build a chatbot from scratch using PySpark * Develop a market-prediction app using stock data * Delve into advanced concepts such as computer vision, neural networks, and deep learning Who this book is for This book is for machine learning practitioners, data scientists, and deep learning enthusiasts who want to take their machine learning skills to the next level by building real-world projects. The intermediate-level guide will help you to implement libraries from the Python ecosystem to build a variety of projects addressing various machine learning domains. Knowledge of Python programming and machine learning concepts will be helpful.

Leverage Docker to unlock efficient and rapid container deployments to improve your development workflow Key Features * Reconfigure Docker hosts to create a logging system with the ElasticSearch-Logstash-Kibana (ELK) stack * Tackle the challenges of large-scale container deployment with this fast-paced guide * Benchmark the performance of your Docker containers using Apache JMeter Book Description Docker is an enterprise-grade container platform that allows you to build and deploy your apps. Its portable format lets you run your code right from your desktop workstations to popular cloud computing providers. This comprehensive guide will improve your Docker work?ows and ensure your application's production environment runs smoothly. This book starts with a refresher on setting up and running Docker and details the basic setup for creating a Docker Swarm cluster. You will then learn how to automate this cluster by using Chef Server and Cookbook. After that, you will run the Docker monitoring system with Prometheus and Grafana, and deploy the ELK stack. You will also learn some tips for optimizing Docker images. After deploying containers with the help of Jenkins, you will then move on to a tutorial on using Apache JMeter to analyze your application's performance. You will learn how to use Docker Swarm and NGINX to load-balance your application and how common debugging tools in Linux can be used to troubleshoot Docker containers. By the end of this book, you will be able to integrate all the optimizations that you have learned and put everything into practice in your applications. What you will learn * Automate provisioning and setting up nodes in a Docker Swarm cluster * Configure a monitoring system with Prometheus and Grafana * Use Apache JMeter to create workloads for benchmarking the performance of Docker containers * Understand how to load-balance an application with Docker Swarm and Nginx * Deploy strace, tcdump, blktrace, and other Linux debugging tools to troubleshoot containers * Integrate Docker optimizations for DevOps, Site Reliability Engineering, CI, and CD Who this book is for If you are a software developer with a good understanding of managing Docker services and the Linux file system and are looking for ways to optimize working with Docker containers, then this is the book for you. Developers fascinated with containers and workflow automation with benefit from this book.