The book opens with an overview of the Spark ecosystem. The book will introduce you to Project Catalyst and Tungsten.
You will understand how Memory Management and Binary Processing, Cache-aware Computation, and Code Generation are used to speed things up dramatically. The book goes on to show how to incorporate H20 and Deeplearning4j for
machine learning and Juypter Notebooks, Zeppelin, Docker and Kubernetes for cloud-based Spark. During the course of the book, you will also learn about the latest enhancements in Apache Spark 2.2, such as using the DataFrame and Dataset APIs exclusively, building advanced, fully automated Machine Learning pipelines with SparkML and perform graph analysis using the new GraphFrames API.
Mastering OpenCV3, Second Edition contains seven chapters, where each chapter is a tutorial for an
entire project from start to finish, based on OpenCV's C++ interface, including the full source code.
The author of each chapter was chosen for their well-regarded online contributions to the OpenCV
community on that topic, and the book was reviewed by one of the main OpenCV developers. Rather
than explaining the basics of OpenCV functions, this book shows how to apply OpenCV to solve
whole problems, including several 3D camera projects (augmented reality, and 3D structure from
Motion) and several facial analysis projects (such as skin detection, simple face and eye detection,
complex facial feature tracking, 3D head orientation estimation, and face recognition), therefore it
makes a great companion to the existing OpenCV books.
Mastering ROS for Robotics Programming is an advanced guide of ROS that is very
suitable for readers who already have a basic knowledge in ROS. ROS is widely used
in robotics companies, universities, and robotics research institutes for designing,
building, and simulating a robot model and interfacing it into real hardware. ROS is
now an essential requirement for Robotic engineers; this guide can help you acquire
knowledge of ROS and can also help you polish your skills in ROS using interactive
examples. Even though it is an advanced guide, you can see the basics of ROS in the
first chapter to refresh the concepts. It also helps ROS beginners. The book mainly
focuses on the advanced concepts of ROS, such as ROS Navigation stack, ROS
MoveIt!, ROS plugins, nodelets, controllers, ROS Industrial, and so on.
In this <em>second</em> <em>edition</em>, you will get to grips with the latest features of OpenStack. Starting with an overview of the OpenStack architecture, you'll see how to adopt the DevOps style of automation while deploying and operating in an OpenStack environment. We'll show you how to create your own OpenStack private cloud. Then you'll learn about various hypervisors and container technology supported by OpenStack. You'll get an understanding about the segregation of compute nodes based on reliability and availability needs. We'll cover various storage types in OpenStack and advanced networking aspects such as SDN and NFV.
Next, you'll understand the OpenStack infrastructure from a cloud user point of view. Moving on, you'll develop troubleshooting skills, and get a comprehensive understanding of services such as high availability and failover in OpenStack. Finally, you will gain experience of running a centralized logging server and monitoring OpenStack services.
The book will show you how to carry out performance tuning based on OpenStack service logs. You will be able to master OpenStack benchmarking and performance tuning. By the end of the book, you'll be ready to take steps to deploy and manage an OpenStack cloud with the latest open source technologies.
Mastering Apache Spark <em>2.x</em> - Second Edition by Romeo Kienzler
English | 26 July 2017 | ISBN: 1786462745 | ASIN: B01MR4YF5G | 354 Pages | AZW3 | 13.74 MB
Advanced analytics on your Big Data with latest Apache Spark <em>2.x</em>
About This Book
An advanced guide with a combination of instructions and practical examples to extend the most up-to date Spark functionalities.
Extend your data processing capabilities to process huge chunk of data in minimum time using advanced concepts in Spark.
Master the art of real-time processing with the help of Apache Spark <em>2.x</em>
Who This Book Is For
If you are a developer with some experience with Spark and want to strengthen your knowledge of how to get around in the world of Spark, then this book is ideal for you. Basic knowledge of Linux, Hadoop and Spark is assumed. Reasonable knowledge of Scala is expected.
What You Will Learn
Examine Advanced Machine Learning and DeepLearning with MLlib, SparkML, SystemML, H2O and DeepLearning4J
Study highly optimised unified batch and real-time data processing using SparkSQL and Structured Streaming
Evaluate large-scale Graph Processing and Analysis using GraphX and GraphFrames
Apply Apache Spark in Elastic deployments using Jupyter and Zeppelin Notebooks, Docker, Kubernetes and the IBM Cloud
Understand internal details of cost based optimizers used in Catalyst, SystemML and GraphFrames
Learn how specific parameter settings affect overall performance of an Apache Spark cluster
Leverage Scala, R and python for your data science projects
Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing, machine learning, stream processing, and SQL. This book aims to take your knowledge of Spark to the next level by teaching you how to expand Spark's functionality and implement your data flows and machine/deep learning programs on top of the platform.
The book commences with an overview of the Spark ecosystem. It will introduce you to Project Tungsten and Catalyst, two of the major advancements of Apache Spark <em>2.x</em>.
You will understand how memory management and binary processing, cache-aware computation, and code generation are used to speed things up dramatically. The book extends to show how to incorporate H20, SystemML, and Deeplearning4j for machine learning, and Jupyter Notebooks and Kubernetes/Docker for cloud-based Spark. During the course of the book, you will learn about the latest enhancements to Apache Spark <em>2.x</em>, such as interactive querying of live data and unifying DataFrames and Datasets.
You will also learn about the updates on the APIs and how DataFrames and Datasets affect SQL, machine learning, graph processing, and streaming. You will learn to use Spark as a big data operating system, understand how to implement advanced analytics on the new APIs, and explore how easy it is to use Spark in day-to-day tasks.
Style and approach
This book is an extensive guide to Apache Spark modules and tools and shows how Spark's functionality can be extended for real-time processing and storage with worked examples.
Mastering Machine Learning with scikit-learn - Second Edition by Gavin Hackeling
English | 24 July 2017 | ASIN: B06ZYRPFMZ | ISBN: 1783988363 | 254 Pages | AZW3 | 5.17 MB
Master popular machine learning models including k-nearest neighbors, random forests, logistic regression, k-means, naive Bayes, and artificial neural networks
Learn how to build and evaluate performance of efficient models using scikit-learn
Practical guide to master your basics and learn from real life applications of machine learning
Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.
This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn's API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model's performance.
By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.
What you will learn
Review fundamental concepts such as bias and variance
Extract features from categorical variables, text, and images
Predict the values of continuous variables using linear regression and K Nearest Neighbors
Classify documents and images using logistic regression and support vector machines
Create ensembles of estimators using bagging and boosting techniques
Discover hidden structures in data using K-Means clustering
Evaluate the performance of machine learning systems in common tasks
About the Author
Gavin Hackeling is a data scientist and author. He was worked on a variety of machine learning problems, including automatic speech recognition, document classification, object recognition, and semantic segmentation. An alumnus of the University of North Carolina and New York University, he lives in Brooklyn with his wife and cat.
Table of Contents
The Fundamentals of Machine Learning
Simple linear regression
Classification and Regression with K Nearest Neighbors
Feature Extraction and Preprocessing
From Simple Regression to Multiple Regression
From Linear Regression to Logistic Regression
Nonlinear Classification and Regression with Decision Trees
From Decision Trees to Random Forests, and other Ensemble Methods
From the Perceptron to Support Vector Machines
From the Perceptron to Artificial Neural Networks
Clustering with K-Means
Dimensionality Reduction with Principal Component Analysis
Mastering Qt 5: Create stunning cross-platform applications using C++ with Qt Widgets and QML with Qt Quick, 2nd Edition – August 27, 2018
An In-depth guide updated with the latest version of Qt 5.11 including new features such as Quick Controls and Qt Gamepad
•Unleash the power of Qt 5.11 with C++
•Build applications using Qt Widgets (C++) or Qt Quick (QML)
•Create cross-platform applications for mobile and desktop platforms with Qt 5
Qt 5.11 is an app development framework that provides a great user experience and develops full capability applications with Qt Widgets, QML, and even Qt 3D. Whether you're building GUI prototypes or fully-fledged cross-platform GUI applications with a native look and feel, Mastering Qt 5 is your fastest, easiest, and most powerful solution. This book addresses various challenges and teaches you to successfully develop cross-platform applications using the Qt framework, with the help of well-organized projects.
Working through this book, you will gain a better understanding of the Qt framework, as well as the tools required to resolve serious issues, such as linking, debugging, and multithreading. You'll start off your journey by discovering the new Qt 5.11 features, soon followed by exploring different platforms and learning to tame them. In addition to this, you'll interact with a gamepad using Qt Gamepad. Each chapter is a logical step for you to complete in order to master Qt.
By the end of this book, you'll have created an application that has been tested and is ready to be shipped.
What you will learn
•Create stunning UIs with Qt Widgets and Qt Quick 2
•Develop powerful, cross-platform applications with the Qt framework
•Design GUIs with the Qt Designer and build a library in it for UI previews
•Handle user interaction with the Qt signal or slot mechanism in C++
•Prepare a cross-platform project to host a third-party library
•Use the Qt Animation framework to display stunning effects
•Deploy mobile apps with Qt and embedded platforms
•Interact with a gamepad using Qt Gamepad
Who this book is for
Mastering Qt 5 is for developers and programmers who want to build GUI-based applications. C++ knowledge is necessary, and knowing QT basics will help you get the most out of this book.
Table of Contents
1.Get Your Qt Feet Wet
2.Discovering qmake Secrets
3.Dividing Your Project and Ruling Your Code
4.Conquering the Desktop UI
5.Dominating the Mobile UI
6.Even Qt Deserves a Slice of Raspberry Pi
7.Third-Party Libraries without a Headache
8.Animations - Its Alive, Alive!
9.Keeping Your Sanity with Multithreading
10.Need IPC? Get Your Minions to Work
11.Having Fun with Multimedia and Serialization
12.You Shall (Not) Pass with QTest
13.All Packed and Ready to Deploy
14.Qt Hat Tips and Tricks
This <em>second</em> <em>edition</em> of Mastering PostgreSQL 11 helps you build dynamic database solutions for enterprise applications using the latest release of PostgreSQL, which enables database analysts to design both the physical and technical aspects of the system architecture with ease.
This book begins with an introduction to the newly released features in PostgreSQL 11 to help you build efficient and fault-tolerant PostgreSQL applications. You'll examine all of the advanced aspects of PostgreSQL in detail, including logical replication, database clusters, performance tuning, monitoring, and user management. You will also work with the PostgreSQL optimizer, configuring PostgreSQL for high speed, and see how to move from Oracle to PostgreSQL. As you progress through the chapters, you will cover transactions, locking, indexes, and optimizing queries to improve performance. Additionally, you'll learn to manage network security and explore backups and replications, while understanding the useful extensions of PostgreSQL so that you can optimize the speed and performance of large databases.
By the end of this book, you will be able to use your database to its utmost capacity by implementing advanced administrative tasks with ease.
The book will show you how to carry out performance tuning based on OpenStack service logs. You will be able to master OpenStack benchmarking and performance tuning. By the end of the book, you\\\'ll be ready to take steps to deploy and manage an OpenStack cloud with the latest open source technologies
Table of Contents
Creating Models with SQLAlchemy
Creating Views with Templates
Creating Controllers with Blueprints
Advanced Application Structure
Securing Your App
Using NoSQL with Flask
Building RESTful APIs
Creating Asynchronous Tasks with Celery
Useful Flask Extensions
Building Your Own Extension
Testing Flask Apps
Deploying Flask Apps
Docker has been a game-changer when it comes to how modern applications are deployed and created. It has now grown into a key driver of innovation beyond system administration, with an impact on the world of web development. But how can you make sure you're keeping up with the innovations it's driving, or be sure you're using it to its full potential? Mastering Docker shows you how; this book not only demonstrates how to use Docker more effectively, but also helps you rethink and reimagine what's possible with it.
You will cover concepts such as building, managing, and storing images, along with best practices to make you confident, before delving more into Docker security. You'll find everything related to extending and integrating Docker in new and innovative ways. Docker Compose, Docker Swarm, and Kubernetes will help you take control of your containers in an efficient manner.
By the end of the book, you will have a broad, yet detailed, sense of what's possible with Docker, and how seamlessly it fits in with a range of other platforms and tools.
Python for Finance - Second Edition
English | 2017 | ISBN-10: 1787125696 | 586 pages | PDF/MOBI/EPUB (conv) | 4.5 Mb
Learn and implement various Quantitative Finance concepts using the popular Python libraries
About This Book
Understand the fundamentals of Python data structures and work with time-series data
Implement key concepts in quantitative finance using popular Python libraries such as NumPy, SciPy, and matplotlib
A step-by-step tutorial packed with many Python programs that will help you learn how to apply Python to finance
Who This Book Is For
This book assumes that the readers have some basic knowledge related to Python. However, he/she has no knowledge of quantitative finance. In addition, he/she has no knowledge about financial data.
What You Will Learn
Become acquainted with Python in the first two chapters
Run CAPM, Fama-French 3-factor, and Fama-French-Carhart 4-factor models
Learn how to price a call, put, and several exotic options
Understand Monte Carlo simulation, how to write a Python program to replicate the Black-Scholes-Merton options model, and how to price a few exotic options
Understand the concept of volatility and how to test the hypothesis that volatility changes over the years
Understand the ARCH and GARCH processes and how to write related Python programs
This book uses Python as its computational tool. Since Python is free, any school or organization can download and use it.
This book is organized according to various finance subjects. In other words, the first <em>edition</em> focuses more on Python, while the <em>second</em> <em>edition</em> is truly trying to apply Python to finance.
The book starts by explaining topics exclusively related to Python. Then we deal with critical parts of Python, explaining concepts such as time value of money stock and bond evaluations, capital asset pricing model, multi-factor models, time series analysis, portfolio theory, options and futures.
This book will help us to learn or review the basics of quantitative finance and apply Python to solve various problems, such as estimating IBM's market risk, running a Fama-French 3-factor, 5-factor, or Fama-French-Carhart 4 factor model, estimating the VaR of a 5-stock portfolio, estimating the optimal portfolio, and constructing the efficient frontier for a 20-stock portfolio with real-world stock, and with Monte Carlo Simulation. Later, we will also learn how to replicate the famous Black-Scholes-Merton option model and how to price exotic options such as the average price call option.
Style and approach
This book takes a step-by-step approach in explaining the libraries and modules in Python, and how they can be used to implement various aspects of quantitative finance. Each concept is explained in depth and supplemented with code examples for better understanding.
Discover the powerful, hidden features of Rust you need to build robust, concurrent, and fast applications About This Book ? Learn how concurrency works in Rust and why it is safe ? Get to know the different philosophies of error handling and how to use them wisely ? After reading this book, you will be able to migrate your legacy C or C++ application to a Rust environment Who This Book Is For The target audience would be readers having knowledge of other programming languages and are able to work fluently in the operating system of their choice, be it Linux, OS X or Windows. Since Rust is a rather new language, they are interested in programming beyond simply using it for work. The book focuses on intermediate and advanced features of Rust. What You Will Learn ? Implement unit testing patterns with the standard Rust tools ? Get to know the different philosophies of error handling and how to use them wisely ? Appreciate Rust's ability to solve memory allocation problems safely without garbage collection ? Get to know how concurrency works in Rust and use concurrency primitives such as threads and message passing ? Use syntax extensions and write your own ? Create a Web application with Rocket ? Use Diesel to build safe database abstractions In Detail If concurrent programs are giving you sleepless nights, Rust is your go-to language. Being one of the first ever comprehensive books on Rust, it is filled with real-world examples and explanations, showing you how you can build scalable and reliable programs for your organization. We’ll teach you intermediate to advanced level concepts that make Rust a great language. Improving performance, using generics, building macros, and working with threads are just some of the topics we’ll cover. We’ll talk about the official toolsets and ways to discover more. The book contains a mix of theory interspersed with hands-on tasks, so you acquire the skills as well as the knowledge. Since programming cannot be learned by just reading, we provide exercises (and solutions) to hammer the concepts in. After reading this book, you will be able to implement Rust for your enterprise project, deploy the software, and will know the best practices of coding in Rust. Style and approach This book is your one stop guide to the Rust programming language and covers advanced-level concepts in a detailed manner using real-world examples.
About the book
Processing data tied to location and topology requires specialized know-how. PostGIS is a free spatial database extender for PostgreSQL, every bit as good as proprietary software. With it, you can easily create location-aware queries in just a few lines of SQL code and build the back end for a mapping, raster analysis, or routing application with minimal effort.
PostGIS in Action, Second Edition teaches you to solve real-world geodata problems. It first gives you a background in vector-, raster-, and topology-based GIS and then quickly moves into analyzing, viewing, and mapping data. You’ll learn how to optimize queries for maximum speed, simplify geometries for greater efficiency, and create custom functions for your own applications. You’ll also learn how to apply your existing GIS knowledge to PostGIS and integrate with other GIS tools.
Familiarity with relational database and GIS concepts is helpful but not required.
An introduction to spatial databases
Geometry, geography, raster, and topology spatial types, functions, and queries
Applying PostGIS to real-world problems
Extending PostGIS to web and desktop applications
Updated for PostGIS <em>2.x</em> and PostgreSQL 9.x
About the authors
Regina Obe and Leo Hsu are database consultants and authors. Regina is a member of the PostGIS core development team and the Project Steering Committee.
Mastering OpenCV 3 - Second Edition by Daniel Lélis Baggio
English | 4 May 2017 | ASIN: B01N7G0BKE | 250 Pages | AZW3 | 4.82 MB
Updated for OpenCV 3, this book covers new features that will help you unlock the full potential of OpenCV 3
Written by a team of 7 experts, each chapter explores a new aspect of OpenCV to help you make amazing computer-vision aware applications
Each chapter is a tutorial for an entire project from start to finish, showing you how to apply OpenCV to solve complete problems
As we become more capable of handling data in every kind, we are becoming more reliant on visual input and what we can do with those self-driving cars, face recognition, and even augmented reality applications and games. This is all powered by Computer Vision.
This book will put you straight to work in creating powerful and unique computer vision applications. Each chapter is structured around a central project and deep dives into an important aspect of OpenCV such as facial recognition, image target tracking, making augmented reality applications, the 3D visualization framework, and machine learning. You’ll learn how to make AI that can remember and use neural networks to help your applications learn.
By the end of the book, you will have created various working prototypes with the projects in the book and will be well versed with the new features of OpenCV3.
What you will learn
Execute basic image processing operations and cartoonify an image
Build an OpenCV project natively with Raspberry Pi and cross-compile it for Raspberry Pi.text
Extend the natural feature tracking algorithm to support the tracking of multiple image targets on a video
Use OpenCV 3’s new 3D visualization framework to illustrate the 3D scene geometry
Create an application for Automatic Number Plate Recognition (ANPR) using a support vector machine and Artificial Neural Networks
Train and predict pattern-recognition algorithms to decide whether an image is a number plate
Use POSIT for the six degrees of freedom head pose
Train a face recognition database using deep learning and recognize faces from that database
pdf 档 Preface C++ is a powerful language. Coupled with Qt, you have in your hands a cross-platform framework that allies performance and ease of use. Qt is a vast framework that provides tools in many areas (GUI, threads, networking, and so on). 25 years after its inception
Mastering OpenStack - Second Edition: Design, deploy, and manage clouds in mid to large IT infrastructures Paperback – April 26, 2017
Discover your complete guide to designing, deploying, and managing OpenStack-based clouds in mid-to-large IT infrastructures with best practices, expert understanding, and more
About This Book
Design and deploy an OpenStack-based cloud in your mid-to-large IT infrastructure using automation tools and best practices
Keep yourself up-to-date with valuable insights into OpenStack components and new services in the latest OpenStack release
Discover how the new features in the latest OpenStack release can help your enterprise and infrastructure
Who This Book Is For
This book is for system administrators, cloud engineers, and system architects who would like to deploy an OpenStack-based cloud in a mid-to-large IT infrastructure. This book requires a moderate level of system administration and familiarity with cloud concepts.
What You Will Learn
Explore the main architecture design of OpenStack components and core-by-core services, and how they work together
Design different high availability scenarios and plan for a no-single-point-of-failure environment
Set up a multinode environment in production using orchestration tools
Boost OpenStack's performance with advanced configuration
Delve into various hypervisors and container technology supported by OpenStack
Get familiar with deployment methods and discover use cases in a real production environment
Adopt the DevOps style of automation while deploying and operating in an OpenStack environment
Monitor the cloud infrastructure and make decisions on maintenance and performance improvement
This book has one goal: to provide a comprehensive introduction to the theoretical and practical aspects of blockchain technology. This book contains all the material that is required to fully understand blockchain technology. After reading this book, readers will be able to develop a deep understanding of inner workings of blockchain technology and will be able to develop blockchain applications. This book covers all topics relevant to blockchain technology, including cryptography, cryptocurrenices, Bitcoin, Ethereum, and various other platforms and tools used for blockchain development.
It is recommended that readers have a basic understanding of computer science and basic programming experience in order to benefit fully from this book. However, if that is not the case then still this book can be read easily, as relevant background material is provided where necessary.
Machine Learning with Spark - Second Edition by Rajdeep Dua
English | 4 May 2017 | ASIN: B01DPR2ELW | 532 Pages | AZW3 | 9.6 MB
Get to the grips with the latest version of Apache Spark
Utilize Spark's machine learning library to implement predictive analytics
Leverage Spark’s powerful tools to load, analyze, clean, and transform your data
This book will teach you about popular machine learning algorithms and their implementation. You will learn how various machine learning concepts are implemented in the context of Spark ML. You will start by installing Spark in a single and multinode cluster. Next you'll see how to execute Scala and Python based programs for Spark ML. Then we will take a few datasets and go deeper into clustering, classification, and regression. Toward the end, we will also cover text processing using Spark ML.
Once you have learned the concepts, they can be applied to implement algorithms in either green-field implementations or to migrate existing systems to this new platform. You can migrate from Mahout or Scikit to use Spark ML.
By the end of this book, you will acquire the skills to leverage Spark's features to create your own scalable machine learning applications and power a modern data-driven business.
What you will learn
Get hands-on with the latest version of Spark ML
Create your first Spark program with Scala and Python
Set up and configure a development environment for Spark on your own computer, as well as on Amazon EC2
Access public machine learning datasets and use Spark to load, process, clean, and transform data
Use Spark's machine learning library to implement programs by utilizing well-known machine learning models
Deal with large-scale text data, including feature extraction and using text data as input to your machine learning models
Write Spark functions to evaluate the performance of your machine learning models
Kubernetes is an open source orchestration platform to manage containers in a cluster environment. With Kubernetes, you can configure and deploy containerized applications easily. This book gives you a quick brush up on how Kubernetes works with containers, and an overview of main Kubernetes concepts, such as Pods, Deployments, Services and etc.
This book explains how to create Kubernetes clusters and run applications with proper authentication and authorization configurations. With real-world recipes, you'll learn how to create high availability Kubernetes clusters on AWS, GCP and in on-premise datacenters with proper logging and monitoring setup. You'll also learn some useful tips about how to build a continuous delivery pipeline for your application. Upon completion of this book, you will be able to use Kubernetes in production and will have a better understanding of how to manage containers using Kubernetes.
Navigate through the complex jungle of components in OpenStack using practical instructions
This book helps administrators, cloud engineers, and even developers to consolidate and control pools of compute, networking, and storage resources
Learn to use the centralized dashboard and administration panel to monitor large-scale deployments
OpenStack is a widely popular platform for cloud computing. Applications that are built for this platform are resilient to failure and convenient to scale. This book, an update to our extremely popular OpenStack Essentials (published in May 2015) will help you master not only the essential bits, but will also examine the new features of the latest OpenStack release - Mitaka; showcasing how to put them to work straight away.
This book begins with the installation and demonstration of the architecture. This book will tech you the core 8 topics of OpenStack. They are Keystone for Identity Management, Glance for Image management, Neutron for network management, Nova for instance management, Cinder for Block storage, Swift for Object storage, Ceilometer for Telemetry and Heat for Orchestration. Further more you will learn about launching and configuring Docker containers and also about scaling them horizontally. You will also learn about monitoring and Troubleshooting OpenStack.
What you will learn
Brush up on the latest release, and how it affects the various components
Install OpenStack using the Packstack and RDO Manager installation tool
Learn to convert a computer node that supports Docker containers
Implement Ceph Block Device images with OpenStack
Create and allocate virtual networks, routers and IP addresses to OpenStack Tenants.
Configuring and Launching a Docker container.
About the Author
Dan Radez joined the OpenStack community in 2012 in an operator role. His experience is focused on installing, maintaining, and integrating OpenStack clusters. He has been given the opportunity to internationally present OpenStack content to a range of audiences of varying expertise. In January 2015, Dan joined the OPNFV community and has been working to integrate RDO Manager with SDN controllers and the networking features necessary for NFV.
Dan's experience includes web application programming, systems release engineering, and virtualization product development. Most of these roles have had an open source community focus to them. In his spare time, Dan enjoys spending time with his wife and three boys, training for and racing triathlons, and tinkering with electronics projects.
Table of Contents
This book is intended for Python developers who are new to OpenCV and want to develop computer vision applications with OpenCV and Python. This book is also useful for generic software developers who want to deploy computer vision applications on the cloud. It would be helpful to have some familiarity with basic mathematical concepts such as vectors and matrices.
CAMEL IN ACTION 2ND EDTION.
The open source Apache Camel project has been at the forefront of the widespread
adoption of Enterprise Integration Patterns on the JVM for many years. In fact it’s
been so popular that some developers of other popular programming languages have
cited it as a strong influence when they’ve implemented similar efforts. Apache Camel’s
easy, intuitive, and extensible approach has made it possible for even novice developers
to produce reliable solutions to complex problems in a realistic period of time.
The vibrant open source community of contributors and users has helped evolve the
project into new areas such as the cloud, mobile, and the Internet of Things (IoT).
This positive feedback loop looks strong. Innovation continues on a daily basis led by
a number of key contributors, most notably the authors of this book, Claus and Jon.
I first heard of Claus and Jon when I became an early user of Apache Camel in a
previous role. Their programming style was clear and concise, matched only by their
patience, ability to communicate complex concepts at all levels, and their insatiable
thirst to learn from the community of Apache Camel users and contributors in order to
continually evolve and grow the project. Fast-forward
a few years, and I was able to work
much more closely with them and the rest of the Fuse team when Red Hat acquired
FuseSource. I've learned that my initial love of Apache Camel was not misplaced, and
we’ve seen huge success internally and externally with it.
Pro Apache Log4j <em>second</em> <em>edition</em> Pro Apache Log4j <em>second</em> <em>edition</em> Pro Apache Log4j <em>second</em> <em>edition</em> Pro Apache Log4j <em>second</em> <em>edition</em> Pro Apache Log4j <em>second</em> <em>edition</em>
Author: Yves Hilpisch
Pub Date: 2019
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the <em>second</em> <em>edition</em> of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics.
Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
Get up to date with the defining characteristics of Spring Boot 2.0 in Spring Framework 5
Learn to perform Reactive programming with SpringBoot
This book covers the latest features, tools, and practices including Spring MVC, REST, Security, AMPQ messaging, and more
Spring Boot provides a variety of features that address today's business needs with a powerful database and state of the art MVC framework. This practical guide will help you get up and running with all the latest features of Spring Boot.
The book starts off by helping you build a simple app, then show you how to bundle and deploy it to the cloud. From here, we take you through reactive programming showing you how to interact with controllers and templates and handle data access. Once you're done, you can start testing using unit tests, slice, and embedded spring boot tests.
We also go into detail about developer tools, messaging, web sockets, security, and deployment. So if you want a good understanding of the core app functionality using Spring Boot, this is the book for you.
This introduction to programming places computer science in the core of a liberal arts education. Unlike other introductory books, it focuses on the program design process. This approach fosters a variety of skills--critical reading, analytical thinking, creative synthesis, and attention to detail--that are important for everyone, not just future computer programmers.
The Reasoned Schemer (MIT Press) (The MIT Press)
By 作者: Daniel P Friedman – William E Byrd – Oleg Kiselyov – Jason Hemann
ISBN-10 书号: 0262535513
ISBN-13 书号: 9780262535519
Edition 版本: <em>second</em> <em>edition</em>
pages 页数: (206)
A new <em>edition</em> of a book, written in a humorous question-and-answer style, that shows how to implement and use an elegant little programming language for logic programming.
The goal of this book is to show the beauty and elegance of relational programming, which captures the essence of logic programming. The book shows how to implement a relational programming language in Scheme, or in any other functional language, and demonstrates the remarkable flexibility of the resulting relational programs. As in the first <em>edition</em>, the pedagogical method is a series of questions and answers, which proceed with the characteristic humor that marked The Little Schemer and The Seasoned Schemer. Familiarity with a functional language or with the first five chapters of The Little Schemer is assumed.
For this <em>second</em> <em>edition</em>, the authors have greatly simplified the programming language used in the book, as well as the implementation of the language. In addition to revising the text extensively, and simplifying and revising the “Laws” and “Commandments,” they have added explicit “Translation” rules to ease translation of Scheme functions into relations.
Since the First Edition
2.Teaching 01d Toys New Tricks
3.Seeing 01d Friends in New Ways
4.Double Your Fun
6.The Fun Never Ends…
7.A Bit Too Much
8.Just a Bit More
10.Under the Hood
A.Connecting the Wires
B.Welcome to the Club