- Table View
- List View
Learning OpenCV 3 Application Development
by Samyak DattaBuild, create, and deploy your own computer vision applications with the power of OpenCV About This Book • This book provides hands-on examples that cover the major features that are part of any important Computer Vision application • It explores important algorithms that allow you to recognize faces, identify objects, extract features from images, help your system make meaningful predictions from visual data, and much more • All the code examples in the book are based on OpenCV 3.1 – the latest version Who This Book Is For This is the perfect book for anyone who wants to dive into the exciting world of image processing and computer vision. This book is aimed at programmers with a working knowledge of C++. Prior knowledge of OpenCV or Computer Vision/Machine Learning is not required. What You Will Learn • Explore the steps involved in building a typical computer vision/machine learning application • Understand the relevance of OpenCV at every stage of building an application • Harness the vast amount of information that lies hidden in images into the apps you build • Incorporate visual information in your apps to create more appealing software • Get acquainted with how large-scale and popular image editing apps such as Instagram work behind the scenes by getting a glimpse of how the image filters in apps can be recreated using simple operations in OpenCV • Appreciate how difficult it is for a computer program to perform tasks that are trivial for human beings • Get to know how to develop applications that perform face detection, gender detection from facial images, and handwritten character (digit) recognition In Detail Computer vision and machine learning concepts are frequently used in practical computer vision based projects. If you're a novice, this book provides the steps to build and deploy an end-to-end application in the domain of computer vision using OpenCV/C++. At the outset, we explain how to install OpenCV and demonstrate how to run some simple programs. You will start with images (the building blocks of image processing applications), and see how they are stored and processed by OpenCV. You'll get comfortable with OpenCV-specific jargon (Mat Point, Scalar, and more), and get to know how to traverse images and perform basic pixel-wise operations. Building upon this, we introduce slightly more advanced image processing concepts such as filtering, thresholding, and edge detection. In the latter parts, the book touches upon more complex and ubiquitous concepts such as face detection (using Haar cascade classifiers), interest point detection algorithms, and feature descriptors. You will now begin to appreciate the true power of the library in how it reduces mathematically non-trivial algorithms to a single line of code! The concluding sections touch upon OpenCV's Machine Learning module. You will witness not only how OpenCV helps you pre-process and extract features from images that are relevant to the problems you are trying to solve, but also how to use Machine Learning algorithms that work on these features to make intelligent predictions from visual data! Style and approach This book takes a very hands-on approach to developing an end-to-end application with OpenCV. To avoid being too theoretical, the description of concepts are accompanied simultaneously by the development of applications. Throughout the course of the book, the projects and practical, real-life examples are explained and developed step by step in sync with the theory.
Learning OpenCV 3 Computer Vision with Python - Second Edition
by Joseph Howse Joe MinichinoUnleash the power of computer vision with Python using OpenCV About This Book * Create impressive applications with OpenCV and Python * Familiarize yourself with advanced machine learning concepts * Harness the power of computer vision with this easy-to-follow guide Who This Book Is For Intended for novices to the world of OpenCV and computer vision, as well as OpenCV veterans that want to learn about what's new in OpenCV 3, this book is useful as a reference for experts and a training manual for beginners, or for anybody who wants to familiarize themselves with the concepts of object classification and detection in simple and understandable terms. Basic knowledge about Python and programming concepts is required, although the book has an easy learning curve both from a theoretical and coding point of view. What You Will Learn * Install and familiarize yourself with OpenCV 3's Python API * Grasp the basics of image processing and video analysis * Identify and recognize objects in images and videos * Detect and recognize faces using OpenCV * Train and use your own object classifiers * Learn about machine learning concepts in a computer vision context * Work with artificial neural networks using OpenCV * Develop your own computer vision real-life application In Detail OpenCV 3 is a state-of-the-art computer vision library that allows a great variety of image and video processing operations. Some of the more spectacular and futuristic features such as face recognition or object tracking are easily achievable with OpenCV 3. Learning the basic concepts behind computer vision algorithms, models, and OpenCV's API will enable the development of all sorts of real-world applications, including security and surveillance. Starting with basic image processing operations, the book will take you through to advanced computer vision concepts. Computer vision is a rapidly evolving science whose applications in the real world are exploding, so this book will appeal to computer vision novices as well as experts of the subject wanting to learn the brand new OpenCV 3.0.0. You will build a theoretical foundation of image processing and video analysis, and progress to the concepts of classification through machine learning, acquiring the technical know-how that will allow you to create and use object detectors and classifiers, and even track objects in movies or video camera feeds. Finally, the journey will end in the world of artificial neural networks, along with the development of a hand-written digits recognition application. Style and approach This book is a comprehensive guide to the brand new OpenCV 3 with Python to develop real-life computer vision applications.
Learning OpenCV 4 Computer Vision with Python 3: Get to grips with tools, techniques, and algorithms for computer vision and machine learning, 3rd Edition
by Joseph Howse Joe MinichinoUpdated for OpenCV 4 and Python 3, this book covers the latest on depth cameras, 3D tracking, augmented reality, and deep neural networks, helping you solve real-world computer vision problems with practical code Key Features Build powerful computer vision applications in concise code with OpenCV 4 and Python 3 Learn the fundamental concepts of image processing, object classification, and 2D and 3D tracking Train, use, and understand machine learning models such as Support Vector Machines (SVMs) and neural networks Book Description Computer vision is a rapidly evolving science, encompassing diverse applications and techniques. This book will not only help those who are getting started with computer vision but also experts in the domain. You'll be able to put theory into practice by building apps with OpenCV 4 and Python 3. You'll start by understanding OpenCV 4 and how to set it up with Python 3 on various platforms. Next, you'll learn how to perform basic operations such as reading, writing, manipulating, and displaying still images, videos, and camera feeds. From taking you through image processing, video analysis, and depth estimation and segmentation, to helping you gain practice by building a GUI app, this book ensures you'll have opportunities for hands-on activities. Next, you'll tackle two popular challenges: face detection and face recognition. You'll also learn about object classification and machine learning concepts, which will enable you to create and use object detectors and classifiers, and even track objects in movies or video camera feed. Later, you'll develop your skills in 3D tracking and augmented reality. Finally, you'll cover ANNs and DNNs, learning how to develop apps for recognizing handwritten digits and classifying a person's gender and age. By the end of this book, you'll have the skills you need to execute real-world computer vision projects. What you will learn Install and familiarize yourself with OpenCV 4's Python 3 bindings Understand image processing and video analysis basics Use a depth camera to distinguish foreground and background regions Detect and identify objects, and track their motion in videos Train and use your own models to match images and classify objects Detect and recognize faces, and classify their gender and age Build an augmented reality application to track an image in 3D Work with machine learning models, including SVMs, artificial neural networks (ANNs), and deep neural networks (DNNs) Who this book is for If you are interested in learning computer vision, machine learning, and OpenCV in the context of practical real-world applications, then this book is for you. This OpenCV book will also be useful for anyone getting started with computer vision as well as experts who want to stay up-to-date with OpenCV 4 and Python 3. Although no prior knowledge of image processing, computer vision or machine learning is required, familiarity with basic Python programming is a must.
Learning OpenDaylight
by Reza ToghraeeA practical guide to building programmable networks using OpenDaylight About This Book • Learn and understand how SDN controllers operate and integrate with networks; this book's step-by-step tutorials will give you a strong foundation in SDN, NVF, and OpenDayLight. • Learn how to map legacy Layer 2/3 networking technologies in the SDN world • Add new services and capabilities to your infrastructure and quickly adopt SDN and NFV within your organization with OpenDayLight. • Integrate and manage software-defined networks efficiently in your organization. • Build innovative network applications with OpenDayLight and save time and resources. Who This Book Is For This book targets network engineers, network programmers and developers, administrators, and anyone with some level of networking experience who'd like to deploy OpenDayLight effectively. Familiarity with the day-to-day operations of computer networks is expected What You Will Learn • Transition from legacy networking to software-defined networking • Learn how SDN controllers work and manage a network using southbound and northbound APIs • Learn how to deploy the OpenDayLight SDN controller and integrate it with virtual switches • Understand the basic design and operation of the OpenDaylight platform • Build simple MD-SAL OpenDaylight applications • Build applications on top of OpenDayLight to trigger network changes based on different events • Integrate OpenStack with OpenDayLight to build a fully managed network • Learn how to build a software-defined datacenter using NFV and service-chaining technologies In Detail OpenDaylight is an open source, software-defined network controller based on standard protocols. It aims to accelerate the adoption of Software-Defined Networking (SDN) and create a solid foundation for Network Functions Virtualization (NFV). SDN is a vast subject; many network engineers find it difficult to get started with using and operating different SDN platforms. This book will give you a practical bridge from SDN theory to the practical, real-world use of SDN in datacenters and by cloud providers. The book will help you understand the features and use cases for SDN, NFV, and OpenDaylight. NFV uses virtualization concepts and techniques to create virtual classes for node functions. Used together, SDN and NFV can elevate the standards of your network architecture; generic hardware-saving costs and the advanced and abstracted software will give you the freedom to evolve your network in the future without having to invest more in costly equipment. By the end of this book, you will have learned how to design and deploy OpenDaylight networks and integrate them with physical network switches. You will also have mastered basic network programming over the SDN fabric. Style and approach This is a step-by-step tutorial aimed at getting you up-to-speed with OpenDayLight and ready to adopt it for your SDN (Software-Defined Networking) and NFV (Network Functions Virtualization) ecosystem.
Learning OpenShift
by Grant ShipleyThis book is ideal for you if you're a developer experienced with the PHP or Java programming languages and have a basic understanding of using the command line.
Learning OpenStack
by Sunil Sarat Alok ShrivastwaSet up and maintain your own cloud-based Infrastructure as a Service (IaaS) using OpenStack About This Book * Build and manage a cloud environment using just four virtual machines * Get to grips with mandatory as well as optional OpenStack components and know how they work together * Leverage your cloud environment to provide Infrastructure as a Service (IaaS) with this practical, step-by-step guide Who This Book Is For This book is targeted at all aspiring administrators, architects, or students who want to build cloud environments using Openstack. Knowledge of IaaS or cloud computing is recommended. What You Will Learn * Get an introduction to OpenStack and its components * Authenticate and authorize the cloud environment using Keystone * Store and retrieve data and images using storage components such as Cinder, Swift, and Glance * Use Nova to build a Cloud Computing fabric controller * Abstract technology-agnostic networks using the Neutron network component * Gain an understanding of optional components such as Ceilometer, Trove, Ironic, Sahara, Barbican, Zaqar, Designate, Manila, and many more * See how all of the OpenStack components collaborate to provide IaaS to users * Create a production-grade OpenStack and automate your OpenStack Cloud In Detail OpenStack is a free and open source cloud computing platform that is rapidly gaining popularity in Enterprise data centres. It is a scalable operating system and is used to build private and public clouds. It is imperative for all the aspiring cloud administrators to possess OpenStack skills if they want to succeed in the cloud-led IT infrastructure space. This book will help you gain a clearer understanding of OpenStack's components and their interaction with each other to build a cloud environment. You will learn to deploy a self-service based cloud using just four virtual machines and standard networking. You begin with an introduction on the basics of cloud computing. This is followed by a brief look into the need for authentication and authorization, the different aspects of dashboards, cloud computing fabric controllers, along with "Networking as a Service" and "Software Defined Networking." Then, you will focus on installing, configuring, and troubleshooting different architectures such as Keystone, Horizon, Nova, Neutron, Cinder, Swift, and Glance. Furthermore, you will see how all of the OpenStack components come together in providing IaaS to users. Finally, you will take your OpenStack cloud to the next level by integrating it with other IT ecosystem elements before automation. By the end of this book, you will be proficient with the fundamentals and application of OpenStack. Style and approach This is a practical step-by-step guide comprising of installation prerequisites and basic troubleshooting instructions to help you build an error-free OpenStack cloud easily.
Learning OpenStack High Availability
by Rishabh SharmaBuild a resilient and scalable OpenStack cloud, using advanced open source tools About This Book * Leverage the power of OpenStack to achieve high availability * Get to grips with concepts such as Galeria Cluster for Glance and Cinder, MariaDB, and validation * Using clustering and high-availability solutions, this book provides a comprehensive plan for you to connect them with Red Hat Enterprise Linux OpenStack Platform Who This Book Is For This book is for OpenStack administrator, cloud administrator, cloud engineer, or cloud developer with some real time understanding of cloud computing, OpenStack and familiarity with Linux command is essential to start with this book. What You Will Learn * Grasp an understanding of what a highly available design should be using RTO, MTTR, and SLA concepts * Set up and configure Galera and RabbitMQ clusters to build an efficient and reliable messaging cluster * Get to know the advanced areas of network load balancing using configurations of HAproxy and keepalived * Control active/passive OpenStack services by setting up a cluster for two or more nodes * Gain a deeper understanding of how OpenStack services work in cooperation with a stateless mode to offer a scalable cloud framework * Configure and run a distributed neutron installation based on openvswitch and different tunneling protocols * Explore the rudimental configuration of different shared storage options and provide backup services of OpenStack * Get acquainted with how an OpenStack-based cloud can survive various failures using network partitioning split brain, automatic failover, and geo-replication * Distribute applications and services among availability zones in OpenStack to achieve maximum uptime and reliability of service * Control and maintain a cloud with key concepts and tools to correctly measure and control the operations of an OpenStack cloud * Get to know more about the relevant HA deployments of OpenStack with use cases In Detail OpenStack is one of the most popular open source cloud computing platforms, and it is used most of all for deploying Infrastructure as a Service (IaaS) solutions. Enabling high availability in OpenStack is a required skill for cloud administrators and cloud engineers in today's world. This book helps you to achieve high availability and resiliency to OpenStack. This means clustering, fencing, load-balancing, distributed networking, leveraging shared storage, automatic failover, and replication. We start with a basic understanding of what a highly available design is meant to achieve in OpenStack and various ways to achieve high availability in OpenStack through simple step-by-step procedures. Through hands-on examples, you will develop a solid knowledge of horizontally-scalable, fault-resistant, and highly-available OpenStack clusters and will be able to apply the techniques from this book in your day-to-day projects. This book also sheds light on the principles of application design for high availability, and monitoring for high availability, with examples. Style and approach This is a step-by-step guide that uses clustering and high-availability solutions available in the market and provides a comprehensive plan to connect them with Red Hat Enterprise Linux OpenStack Platform to make you a competent OpenStack administrator.
Learning OpenStack Networking: Build a solid foundation in virtual networking technologies for OpenStack-based clouds, 3rd Edition
by James DentonDiscover the basics of virtual networking in OpenStack to implement various cloud network architecturesKey FeaturesLearn the difference between Open vSwitch and Linux bridge switching technologiesConnect virtual machine instances to virtual networks, subnets, and portsImplement virtual load balancers, firewalls, and routers in your networkBook DescriptionOpenStack Networking is a pluggable, scalable, and API-driven system to manage physical and virtual networking resources in an OpenStack-based cloud. Like other core OpenStack components, OpenStack Networking can be used by administrators and users to increase the value and maximize the use of existing datacenter resources. This third edition of Learning OpenStack Networking walks you through the installation of OpenStack and provides you with a foundation that can be used to build a scalable and production-ready OpenStack cloud.In the initial chapters, you will review the physical network requirements and architectures necessary for an OpenStack environment that provide core cloud functionality. Then, you’ll move through the installation of the new release of OpenStack using packages from the Ubuntu repository. An overview of Neutron networking foundational concepts, including networks, subnets, and ports will segue into advanced topics such as security groups, distributed virtual routers, virtual load balancers, and VLAN tagging within instances.By the end of this book, you will have built a network infrastructure for your cloud using OpenStack Neutron.What you will learnGet familiar with Neutron constructs, including agents and pluginsBuild foundational Neutron resources to provide connectivity to instancesWork with legacy Neutron routers and troubleshoot traffic through themExplore high-availability routing capabilities utilizing Virtual Router Redundancy Protocol (VRRP)Create and manage load balancers and associated componentsManage security groups as a method of securing traffic to and from instancesWho this book is forIf you are an OpenStack-based cloud operator and administrator who is new to Neutron networking and wants to build your very own OpenStack cloud, then this book is for you.Prior networking experience and a physical server and network infrastructure is recommended to follow along with concepts demonstrated in the book.
Learning OpenStack Networking (Neutron)
by James DentonIf you are an OpenStack-based cloud operator with experience in OpenStack Compute and nova-network but are new to Neutron networking, then this book is for you. Some networking experience is recommended, and a physical network infrastructure is required to provide connectivity to instances and other network resources configured in the book.
Learning OpenStack Networking (Neutron) - Second Edition
by James DentonIf you are an OpenStack-based cloud operator and administrator who is new to Neutron networking and wants to build your very own OpenStack cloud, then this book is for you. Prior networking experience and a physical server and network infrastructure is recommended to follow along with concepts demonstrated in the book.
Learning OpenTelemetry
by Ted Young Austin ParkerOpenTelemetry is a revolution in observability data. Instead of running multiple uncoordinated pipelines, OpenTelemetry provides users with a single integrated stream of data, providing multiple sources of high-quality telemetry data: tracing, metrics, logs, RUM, eBPF, and more. This practical guide shows you how to set up, operate, and troubleshoot the OpenTelemetry observability system.Authors Austin Parker, head of developer relations at Lightstep and OpenTelemetry Community Maintainer, and Ted Young, cofounder of the OpenTelemetry project, cover every OpenTelemetry component, as well as observability best practices for many popular cloud, platform, and data services such as Kubernetes and AWS Lambda. You'll learn how OpenTelemetry enables OSS libraries and services to provide their own native instrumentation—a first in the industry.Ideal for application developers, OSS maintainers, operators and infrastructure teams, and managers and team leaders, this book guides you through:The principles of modern observabilityAll OpenTelemetry components—and how they fit togetherA practical approach to instrumenting platforms and applicationsMethods for installing, operating, and troubleshooting an OpenTelemetry-based observability solutionWays to roll out and maintain end-to-end observability across a large organizationHow to write and maintain consistent, high-quality instrumentation without a lot of work
Learning Oracle PL/SQL
by Bill PribylDesigned for both new programmers and those experienced in other languages, this book presents the core features of Oracle's PL/SQL language in an easy-to-read format. Learning Oracle PL/SQL will bring programmers up to speed on the most important aspects of PL/SQL, including web and Internet programming. Updated through Oracle9i, includes sample programs downloadable from examples.oreilly.com/learnoracle .
Learning Oracle PL/SQL
by Bill PribylPL/SQL, Oracle's programming language for stored procedures, delivers a world of possibilities for your database programs. PL/SQL supplements the standard relational database language, SQL, with a wide range of procedural features, including loops, IF-THEN statements, advanced data structures, and rich transactional control--all closely integrated with the Oracle database server. Knowing where to start with Oracle's procedural language is not always obvious to a newcomer, especially considering the language's feature set and the sheer size of the official documentation (not to mention Oracle's ever-increasing number of pre-built PL/SQL programs). But Learning Oracle PL/SQL offers the signposts and guidance you need to come up to speed on the language, delivered in a manageable number of pages while covering all the essentials. Topics include: PL/SQL--what is it, and why use it? Why use PL/SQL instead of Java? Syntax and examples of all core language constructs Creating, using, and reusing stored procedures, functions, and packages Building web-based applications using PL/SQL features available "out of the box" (such as PL/SQL Server Pages) Securing PL/SQL programs against attack Benefits of third-party developer tools and integrated development environments Connecting PL/SQL to email, Java, and the Internet Meticulously crafted with all-new examples downloadable from examples.oreilly.com/learnoracle , the book addresses language features available in all versions of Oracle, from Oracle7 to Oracle8i to Oracle9i. Learning Oracle PL/SQL was written by PL/SQL experts Bill Pribyl and Steven Feuerstein, whose easy-to-read style and attention to detail has made other O'Reilly books (such as the bestselling Oracle PL/SQL Programming ) very popular among Oracle developers worldwide. Learning Oracle PL/SQL is meant for a wide range of target audiences, including both beginning programmers and those already experienced with other programming languages. Whether you are a new developer, a crossover programmer from another database system, or a new database administrator who needs to learn PL/SQL, this book will get you well on your way. It is the perfect introduction to Oracle PL/SQL Programming , also by Pribyl and Feuerstein.
Learning pandas
by Michael HeydtIf you are a Python programmer who wants to get started with performing data analysis using pandas and Python, this is the book for you. Some experience with statistical analysis would be helpful but is not mandatory.
Learning pandas
by Michael Heydt<P><P>Key Features <P><P>Employ the use of pandas for data analysis closely to focus more on analysis and less on programming <P><P>Get programmers comfortable in performing data exploration and analysis on Python using pandas <P><P>Step-by-step demonstration of using Python and pandas with interactive and incremental examples to facilitate learning <P><P>Book Description <P><P>This learner's guide will help you understand how to use the features of pandas for interactive data manipulation and analysis. <P><P>This book is your ideal guide to learning about pandas, all the way from installing it to creating one- and two-dimensional indexed data structures, indexing and slicing-and-dicing that data to derive results, loading data from local and Internet-based resources, and finally creating effective visualizations to form quick insights. You start with an overview of pandas and NumPy and then dive into the details of pandas, covering pandas' Series and DataFrame objects, before ending with a quick review of using pandas for several problems in finance. <P><P>With the knowledge you gain from this book, you will be able to quickly begin your journey into the exciting world of data science and analysis. <P><P>What You Will Learn <P><P>Install pandas on Windows, Mac, and Linux using the Anaconda Python distribution <P><P>Learn how pandas builds on NumPy to implement flexible indexed data <P><P>Adopt pandas' Series and DataFrame objects to represent one- and two-dimensional data constructs <P><P>Index, slice, and transform data to derive meaning from information <P><P>Load data from files, databases, and web services <P><P>Manipulate dates, times, and time series data <P><P>Group, aggregate, and summarize data <P><P>Visualize techniques for pandas and statistical data
Learning pandas - Second Edition
by Michael HeydtGet to grips with pandas—a versatile and high-performance Python library for data manipulation, analysis, and discovery About This Book • Get comfortable using pandas and Python as an effective data exploration and analysis tool • Explore pandas through a framework of data analysis, with an explanation of how pandas is well suited for the various stages in a data analysis process • A comprehensive guide to pandas with many of clear and practical examples to help you get up and using pandas Who This Book Is For This book is ideal for data scientists, data analysts, Python programmers who want to plunge into data analysis using pandas, and anyone with a curiosity about analyzing data. Some knowledge of statistics and programming will be helpful to get the most out of this book but not strictly required. Prior exposure to pandas is also not required. What You Will Learn • Understand how data analysts and scientists think about of the processes of gathering and understanding data • Learn how pandas can be used to support the end-to-end process of data analysis • Use pandas Series and DataFrame objects to represent single and multivariate data • Slicing and dicing data with pandas, as well as combining, grouping, and aggregating data from multiple sources • How to access data from external sources such as files, databases, and web services • Represent and manipulate time-series data and the many of the intricacies involved with this type of data • How to visualize statistical information • How to use pandas to solve several common data representation and analysis problems within finance In Detail You will learn how to use pandas to perform data analysis in Python. You will start with an overview of data analysis and iteratively progress from modeling data, to accessing data from remote sources, performing numeric and statistical analysis, through indexing and performing aggregate analysis, and finally to visualizing statistical data and applying pandas to finance. With the knowledge you gain from this book, you will quickly learn pandas and how it can empower you in the exciting world of data manipulation, analysis and science. Style and approach • Step-by-step instruction on using pandas within an end-to-end framework of performing data analysis • Practical demonstration of using Python and pandas using interactive and incremental examples
Learning Path – Getting Started with Tableau 10: Transform Your Business With Rich Data Visualizations And Interactive Dashboards With Tableau 10
by Donabel Santos Joshua MilliganGetting Started with Tableau 10 is designed for business intelligence users and data analysts who want to expand their data visualization knowledge by learning Tableau 10.
Learning Path - Apache Spark 2: Master Complex Big Data Processing, Stream Analytics, And Machine Learning With Apache Spark
by Meenakshi Rajendran Siamak Amirghodsi Sridhar Alla Md. Rezaul Karim Romeo KienzlerIf you are an intermediate-level Spark developer looking to master the advanced capabilities and use-cases of Apache Spark 2.x, this Learning Path is ideal for you. Big data professionals who want to learn how to integrate and use the features of Apache Spark and build a strong big data pipeline will also find this Learning Path useful. To grasp the concepts explained in this Learning Path, you must know the fundamentals of Apache Spark and Scala.
Learning Path - C# 7 and .NET: The Open Source Revolution Of . Net Core
by Ovais Mehboob Khan Mark J. PriceThis Learning Path is designed for developers who want to gain a solid foundation with C# and .NET Core, and want to build cross-platform applications. To gain maximum benefits from this Learning Path, you must have the basic knowledge of C#.
Learning Path - Complete Python Web Development with Django: Get hands-on with Python Programming and Django web development
by Arun Ravindran Gaston C. Hillar Antonio MeleThis Learning Path is designed for Python developers who want to create robust web apps with Django. Though you need a basic working knowledge of Django, you do not need any previous experience with RESTful web services or Python.
Learning Path - Complete Vue.js 2 Web Development: Practical Guide To Building End-to-end Web Development Solutions With Vue. Js 2
by Paul Halliday Andrea Passaglia Mike StreetThe Learning Path is intended for JavaScript developers at any level of expertise who wants to learn Vue.js and develop productive web applications with the power of the latest Vue.js.
Learning Path - Deploying Azure Solutions: A Complete Guide To Cloud Development Using Microsoft Azure
by Ritesh Modi Oliver Michalski Jan-Henrik Damaschke Florian KlaffenbachDeploying Azure Solutions is for IT architects, system and network admins, and DevOps engineers who are aware of Azure solutions and want to implement them for their organization. Prior basic knowledge of the Azure Cloud platform is good to have.
Learning Path - Getting Started with Blockchain: Develop Smart Applications With Blockchain Technologies - Ethereum, Javascript, Hyperledger Fabric, And Corda
by Narayan Prusty Paul Valencourt Samanyu Chopra Brenn HillGetting Started with Blockchain is for you if you want to get to grips with the blockchain technology and develop your own distributed applications. It is also designed for those who want to polish their existing knowledge regarding the various pillars of the blockchain ecosystem. Prior exposure to an object-oriented programming language such as JavaScript is needed.
Learning Path - Getting Started with Spring Microservices: Master design patterns of the Spring framework to build smart, efficient microservices
by Dinesh Rajput Rajesh R VGetting 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.
Learning Path - Microsoft PowerBI Complete Reference: Bring Your Data To Life With The Powerful Features Of Microsoft Power Bi
by Brett Powell Manuel Quintana Mitchell Pearson Brian Knight Devin KnightMicrosoft Power BI Complete Reference Guide is for those who want to learn and use the Power BI features to extract maximum information and make intelligent decisions that boost their business. If you have a basic understanding of BI concepts and want to learn how to apply them using Microsoft Power BI, then Learning Path is for you. It consists of real-world examples on Power BI and goes deep into the technical issues, covers additional protocols, and much more.