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Infrastructure as Code (IAC) Cookbook

Author : Stephane Jourdan
Publisher : Packt Publishing Ltd
ISBN 13 : 1786461293
Total Pages : 440 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Infrastructure as Code (IAC) Cookbook by : Stephane Jourdan

Download or read book Infrastructure as Code (IAC) Cookbook written by Stephane Jourdan and published by Packt Publishing Ltd. This book was released on 2017-02-17 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: Over 90 practical, actionable recipes to automate, test, and manage your infrastructure quickly and effectively About This Book Bring down your delivery timeline from days to hours by treating your server configurations and VMs as code, just like you would with software code. Take your existing knowledge and skill set with your existing tools (Puppet, Chef, or Docker) to the next level and solve IT infrastructure challenges. Use practical recipes to use code to provision and deploy servers and applications and have greater control of your infrastructure. Who This Book Is For This book is for DevOps engineers and developers working in cross-functional teams or operations and would now switch to IAC to manage complex infrastructures. What You Will Learn Provision local and remote development environments with Vagrant Automate production infrastructures with Terraform, Ansible and Cloud-init on AWS, OpenStack, Google Cloud, Digital Ocean, and more Manage and test automated systems using Chef and Puppet Build, ship, and debug optimized Docker containers Explore the best practices to automate and test everything from cloud infrastructures to operating system configuration In Detail Infrastructure as Code (IAC) is a key aspect of the DevOps movement, and this book will show you how to transform the way you work with your infrastructure—by treating it as software. This book is dedicated to helping you discover the essentials of infrastructure automation and its related practices; the over 90 organized practical solutions will demonstrate how to work with some of the very best tools and cloud solutions. You will learn how to deploy repeatable infrastructures and services on AWS, OpenStack, Google Cloud, and Digital Ocean. You will see both Ansible and Terraform in action, manipulate the best bits from cloud-init to easily bootstrap instances, and simulate consistent environments locally or remotely using Vagrant. You will discover how to automate and test a range of system tasks using Chef or Puppet. You will also build, test, and debug various Docker containers having developers' interests in mind. This book will help you to use the right tools, techniques, and approaches to deliver working solutions for today's modern infrastructure challenges. Style and approach This is a recipe-based book that allows you to venture into some of the most cutting-edge practices and techniques about IAC and solve immediate problems when trying to implement them.

Chef Cookbook

Author : Matthias Marschall
Publisher : Packt Publishing Ltd
ISBN 13 : 1786465663
Total Pages : 269 pages
Book Rating : 4.7/5 (864 download)

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Book Synopsis Chef Cookbook by : Matthias Marschall

Download or read book Chef Cookbook written by Matthias Marschall and published by Packt Publishing Ltd. This book was released on 2017-02-03 with total page 269 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master over 80 incredibly effective recipes to manage the day-to-day complications in your infrastructure About This Book Immediately apply Devops techniques and methods, then combine them with powerful Chef tools to manage and automate your infrastructure Address the growing challenges of code management, cloud, and virtualization with Chef quickly Explore and implement the important aspects of Chef Automate using this recipe-based guide Who This Book Is For This book is for system engineers and administrators who have a fundamental understanding of information management systems and infrastructure. It is also for DevOps Engineers, IT professionals, and organizations who want to automate and gain greater control of their infrastructures with Chef. No experience with Chef is needed, but may help. What You Will Learn Test your cookbooks with Test Kitchen Manage cookbook dependencies with Berkshelf Use reporting to keep track of what happens during the execution of chef-client runs across all of the machines Create custom Ohai and Knife plugins Build a high-availability service using Heartbeat Use a HAProxy to load-balance multiple web servers In Detail Chef is a configuration management tool that lets you automate your more cumbersome IT infrastructure processes and control a large network of computers (and virtual machines) from one master server. This book will help you solve everyday problems with your IT infrastructure with Chef. It will start with recipes that show you how to effectively manage your infrastructure and solve problems with users, applications, and automation. You will then come across a new testing framework, InSpec, to test any node in your infrastructure. Further on, you will learn to customize plugins and write cross-platform cookbooks depending on the platform. You will also install packages from a third-party repository and learn how to manage users and applications. Toward the end, you will build high-availability services and explore what Habitat is and how you can implement it. Style and approach This book follows a recipe-based approach and covers all the important topics you need to know. If you don't want to dig through a whole book before you get started, this book is for you, as it features a set of independent recipes you can try out immediately.

Outsmarting Your Kids Online

Author : Amber Mac
Publisher : Ambermac Media, Incorporated
ISBN 13 : 9780692682692
Total Pages : 202 pages
Book Rating : 4.6/5 (826 download)

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Book Synopsis Outsmarting Your Kids Online by : Amber Mac

Download or read book Outsmarting Your Kids Online written by Amber Mac and published by Ambermac Media, Incorporated. This book was released on 2016-04-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this book, tech expert Amber Mac and Internet security expert Michael Bazzell provide the ultimate handbook for parenting in today's digital world. From understanding social media concerns to learning about tomorrow's technology trends; this book empowers overwhelmed parents to make smarter online decisions to properly protect their kids.

Getting started with z/OS Container Extensions and Docker

Author : Lydia Parziale
Publisher : IBM Redbooks
ISBN 13 : 0738458155
Total Pages : 270 pages
Book Rating : 4.7/5 (384 download)

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Book Synopsis Getting started with z/OS Container Extensions and Docker by : Lydia Parziale

Download or read book Getting started with z/OS Container Extensions and Docker written by Lydia Parziale and published by IBM Redbooks. This book was released on 2021-07-12 with total page 270 pages. Available in PDF, EPUB and Kindle. Book excerpt: IBM® z/OS® Container Extensions (IBM zCX) is a new feature of the next version of the IBM z/OS Operating System (z/OS V2.4). It makes it possible to run Linux on IBM Z® applications that are packaged as Docker container images on z/OS. Application developers can develop, and data centers can operate, popular open source packages, Linux applications, IBM software, and third-party software together with z/OS applications and data. This IBM Redbooks® publication helps you to understand the concepts, business perspectives and reference architecture for installing, tailoring, and configuring zCX in your own environment.

Mastering Hyperledger Fabric

Author : Narendranath Reddy Thota
Publisher : Narendranath Reddy
ISBN 13 :
Total Pages : 295 pages
Book Rating : 4./5 ( download)

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Book Synopsis Mastering Hyperledger Fabric by : Narendranath Reddy Thota

Download or read book Mastering Hyperledger Fabric written by Narendranath Reddy Thota and published by Narendranath Reddy. This book was released on 2020-04-05 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: Mastering Hyperledger Fabric. A one-stop solution to become Master in the Hyperledger Fabric Key Features Detailed Explanation of One way TLS and mutual TLS Detailed Explanation of docker sockets (docker.sock) Exposed functionalities of Fabric CLI’s and SDK’s Enterprise-level chaincode development A glimpse of Hyperledger Fabric 2.0 Advanced examples of Node and golang Fabric SDK Onboard new organization using Node.js SDK (No more CLI) CI/CD for chaincode (Install chaincode directly onto peers from GitHub using Node.js) Fabric setup explanation with Different real-time use cases Deployment of Hyperledger Fabric using docker swarm and Kubernetes Setup and configure caliper to check benchmarks Monitor consortium with Prometheus and grafana Monitor docker and docker swarm using swarmpit and logspout Logging consortium with ELK/EFK stack Some interesting open-source tools and some Bonus concepts Table of Contents Chapter1: Introduction to the Hyperledger Landscape Chapter2: The Disruptive Potential of TLS Chapter3: All about docker sockets Chapter4: Installation Guide Of Prerequisites Chapter5: All about fabric CLI Chapter6: All about SDK's (go lang and Node.js) Chapter7: Advanced Chaincode Development Chapter8: End to End fabric consortium with Solo consensus using docker with one use case Chapter9: End to End fabric Consortium with Kafka consensus using docker swarm with one use case Chapter10: End to End fabric Consortium with Raft consensus using Kubernetes with one use case Chapter11: Private Data Concepts, Consortium level ACL(Access Control Lists) and raft consensus mechanism Chapter12: Setup and Benchmark Blockchain Consortium Using Caliper Chapter13: Monitoring Consortium with Prometheus and grafana Chapter14: Logging Consortium with ELK Stack Chapter15: Glimpse of Hyperledger fabric 2.0 Chapter16: Some Interesting tools Who this Book is For This Book benefits Software Engineers who are ready to shift their focus to distributed technologies and Blockchain. This book provides a comprehensive view of Solution Architecture, so it will be easy for architects to architect their solution. CTO’s around the world want to add hyperledger fabric to their technology stack. Managers to cope up with the latest trend. Faculty Professors in order to get industry insights. Even Engineering Students who want to be ready with the latest technologies. Book Description Mastering Hyperledger Fabric is a craving topic for all Hyperledger Fabric Developers around the world. Hyperledger Fabric is an open-source project that helps organizations create and maintain permissioned distributed Blockchain consortiums. This book is for readers who are looking for Hyperledger offerings to build end-to-end projects with growing complexity and functionalities. This book will be a one-stop solution for all developers who want to build blockchain consortiums using Hyperledger Fabric. Topics include TLS, Unix sockets, caliper(Benchmark tool), raft consensus, advanced chaincode development, key collision and MVCC, chaincode access controls, chaincode encryption, node.js SDK, golang SDK, docker daemon API, private data concepts, onboarding organizations using node.js SDK, deploy hyperledger fabric using Kubernetes, deploy hyperledger fabric using docker swarm, monitoring hyperledger fabric, monitoring Kubernetes, monitoring docker swarm, logging hyperledger fabric. After reading this book the reader will be able to set up Production grade hyperledger fabric consortium using raft consensus mechanisms with monitoring using Prometheus and grafana, even logging. This book explains so many key concepts of hyperledger fabric including 2.0 and written with three years of hyperledger fabric production experience.

Hands-On Machine Learning on Google Cloud Platform

Author : Giuseppe Ciaburro
Publisher : Packt Publishing Ltd
ISBN 13 : 1788398874
Total Pages : 489 pages
Book Rating : 4.7/5 (883 download)

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Book Synopsis Hands-On Machine Learning on Google Cloud Platform by : Giuseppe Ciaburro

Download or read book Hands-On Machine Learning on Google Cloud Platform written by Giuseppe Ciaburro and published by Packt Publishing Ltd. This book was released on 2018-04-30 with total page 489 pages. Available in PDF, EPUB and Kindle. Book excerpt: Unleash Google's Cloud Platform to build, train and optimize machine learning models Key Features Get well versed in GCP pre-existing services to build your own smart models A comprehensive guide covering aspects from data processing, analyzing to building and training ML models A practical approach to produce your trained ML models and port them to your mobile for easy access Book Description Google Cloud Machine Learning Engine combines the services of Google Cloud Platform with the power and flexibility of TensorFlow. With this book, you will not only learn to build and train different complexities of machine learning models at scale but also host them in the cloud to make predictions. This book is focused on making the most of the Google Machine Learning Platform for large datasets and complex problems. You will learn from scratch how to create powerful machine learning based applications for a wide variety of problems by leveraging different data services from the Google Cloud Platform. Applications include NLP, Speech to text, Reinforcement learning, Time series, recommender systems, image classification, video content inference and many other. We will implement a wide variety of deep learning use cases and also make extensive use of data related services comprising the Google Cloud Platform ecosystem such as Firebase, Storage APIs, Datalab and so forth. This will enable you to integrate Machine Learning and data processing features into your web and mobile applications. By the end of this book, you will know the main difficulties that you may encounter and get appropriate strategies to overcome these difficulties and build efficient systems. What you will learn Use Google Cloud Platform to build data-based applications for dashboards, web, and mobile Create, train and optimize deep learning models for various data science problems on big data Learn how to leverage BigQuery to explore big datasets Use Google’s pre-trained TensorFlow models for NLP, image, video and much more Create models and architectures for Time series, Reinforcement Learning, and generative models Create, evaluate, and optimize TensorFlow and Keras models for a wide range of applications Who this book is for This book is for data scientists, machine learning developers and AI developers who want to learn Google Cloud Platform services to build machine learning applications. Since the interaction with the Google ML platform is mostly done via the command line, the reader is supposed to have some familiarity with the bash shell and Python scripting. Some understanding of machine learning and data science concepts will be handy

Hands-On Artificial Intelligence for Beginners

Author : Patrick D. Smith
Publisher : Packt Publishing Ltd
ISBN 13 : 1788992261
Total Pages : 349 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Hands-On Artificial Intelligence for Beginners by : Patrick D. Smith

Download or read book Hands-On Artificial Intelligence for Beginners written by Patrick D. Smith and published by Packt Publishing Ltd. This book was released on 2018-10-31 with total page 349 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grasp the fundamentals of Artificial Intelligence and build your own intelligent systems with ease Key FeaturesEnter the world of AI with the help of solid concepts and real-world use casesExplore AI components to build real-world automated intelligenceBecome well versed with machine learning and deep learning conceptsBook Description Virtual Assistants, such as Alexa and Siri, process our requests, Google's cars have started to read addresses, and Amazon's prices and Netflix's recommended videos are decided by AI. Artificial Intelligence is one of the most exciting technologies and is becoming increasingly significant in the modern world. Hands-On Artificial Intelligence for Beginners will teach you what Artificial Intelligence is and how to design and build intelligent applications. This book will teach you to harness packages such as TensorFlow in order to create powerful AI systems. You will begin with reviewing the recent changes in AI and learning how artificial neural networks (ANNs) have enabled more intelligent AI. You'll explore feedforward, recurrent, convolutional, and generative neural networks (FFNNs, RNNs, CNNs, and GNNs), as well as reinforcement learning methods. In the concluding chapters, you'll learn how to implement these methods for a variety of tasks, such as generating text for chatbots, and playing board and video games. By the end of this book, you will be able to understand exactly what you need to consider when optimizing ANNs and how to deploy and maintain AI applications. What you will learnUse TensorFlow packages to create AI systemsBuild feedforward, convolutional, and recurrent neural networksImplement generative models for text generationBuild reinforcement learning algorithms to play gamesAssemble RNNs, CNNs, and decoders to create an intelligent assistantUtilize RNNs to predict stock market behaviorCreate and scale training pipelines and deployment architectures for AI systemsWho this book is for This book is designed for beginners in AI, aspiring AI developers, as well as machine learning enthusiasts with an interest in leveraging various algorithms to build powerful AI applications.

Hands-On Serverless Computing

Author : Kuldeep Chowhan
Publisher : Packt Publishing Ltd
ISBN 13 : 178883495X
Total Pages : 339 pages
Book Rating : 4.7/5 (888 download)

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Book Synopsis Hands-On Serverless Computing by : Kuldeep Chowhan

Download or read book Hands-On Serverless Computing written by Kuldeep Chowhan and published by Packt Publishing Ltd. This book was released on 2018-07-23 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deploy functions efficiently using different cloud-based serverless offerings Key Features Understand the concept of Function-as-a-Service Implement Serverless solutions using AWS Lambda, Azure Functions and Google Cloud Functions Practical approach towards choosing the best tool for your serverless environment Book Description Serverless applications and architectures are gaining momentum and are increasingly being used by companies of all sizes. Serverless software takes care of many problems that developers face when running systems and servers, such as fault tolerance, centralized logging, horizontal scalability, and deployments. You will learn how to harness serverless technology to rapidly reduce production time and minimize your costs, while still having the freedom to customize your code, without hindering functionality. Upon finishing the book, you will have the knowledge and resources to build your own serverless application hosted in AWS, Microsoft Azure, or Google Cloud Platform, and will have experienced the benefits of event-driven technology for yourself. This hands-on guide dives into the basis of serverless architectures and how to build them using Node.js as a programming language, Visual Studio Code for code editing, and Postman for quickly and securely developing applications without the hassle of configuring and maintaining infrastructure on three public cloud platforms. What you will learn Understand the benefts of serverless computing and know when to use it Develop serverless applications on AWS, Azure, and Google Cloud Get to grips with Function as a Service (FaaS) Apply triggers to serverless functions Build event-driven apps using serverless frameworks Use the Node.js programming language to build serverless apps Use code editors, such as Visual Studio Code, as development environments Master the best development practices for creating scalable and practical solutions Who this book is for This book is targeted towards developers, system administrators or any stakeholder working in the Serverless environment and want to understand how functions work. Basic idea of serverless architecture can be an added advantage

Understanding NFS

Author : Sujata Biswas
Publisher : Sujata Biswas
ISBN 13 :
Total Pages : 34 pages
Book Rating : 4./5 ( download)

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Book Synopsis Understanding NFS by : Sujata Biswas

Download or read book Understanding NFS written by Sujata Biswas and published by Sujata Biswas. This book was released on 2017-12-15 with total page 34 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides you all the information to configure an NFS server-client setup. The content of the book is as follows: Chapter 1: What is NFS? TCP Primer NFS Primer NFS Theory Chapter 2: Pre-Installation Activities and Installation of NFS server and client Documentation Installation of NFS server on Centos But why a same set of users was created in the Server and the Client? Chapter 3 Advanced NFS configuration Setting up an Ubuntu Server-Client NFS configuration with advanced options Chapter 4 Administrative tasks on the client Checking the size of the mounted directories Unmounting a shared directory Boot time mounting of the remote NFS directory. Chapter: 5 Troubleshooting NFS Why do I get the “device is busy” error when I try to unmount a directory on the client? When I try to umount on the client , I get the error “umount failed: Operation not permitted” ? I have weird problems while trying to mount directories on the client, why do I get a process hang? Which Commands should I use for troubleshooting NFS issues? How do I implement AutoFS ?

Deep Learning with Python

Author : Francois Chollet
Publisher : Simon and Schuster
ISBN 13 : 1638352046
Total Pages : 597 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with Python by : Francois Chollet

Download or read book Deep Learning with Python written by Francois Chollet and published by Simon and Schuster. This book was released on 2017-11-30 with total page 597 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models. By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François Chollet works on deep learning at Google in Mountain View, CA. He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework. He also does deep-learning research, with a focus on computer vision and the application of machine learning to formal reasoning. His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance

Robot Operating System (ROS)

Author : Anis Koubaa
Publisher : Springer
ISBN 13 : 3319915908
Total Pages : 604 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Robot Operating System (ROS) by : Anis Koubaa

Download or read book Robot Operating System (ROS) written by Anis Koubaa and published by Springer. This book was released on 2018-07-05 with total page 604 pages. Available in PDF, EPUB and Kindle. Book excerpt: Building on the successful first and second volumes, this book is the third volume of the Springer book on the Robot Operating System (ROS): The Complete Reference. The Robot Operating System is evolving from year to year with a wealth of new contributed packages and enhanced capabilities. Further, the ROS is being integrated into various robots and systems and is becoming an embedded technology in emerging robotics platforms. The objective of this third volume is to provide readers with additional and comprehensive coverage of the ROS and an overview of the latest achievements, trends and packages developed with and for it. Combining tutorials, case studies, and research papers, the book consists of sixteen chapters and is divided into five parts. Part 1 presents multi-robot systems with the ROS. In Part 2, four chapters deal with the development of unmanned aerial systems and their applications. In turn, Part 3 highlights recent work related to navigation, motion planning and control. Part 4 discusses recently contributed ROS packages for security, ROS2, GPU usage, and real-time processing. Lastly, Part 5 deals with new interfaces allowing users to interact with robots. Taken together, the three volumes of this book offer a valuable reference guide for ROS users, researchers, learners and developers alike. Its breadth of coverage makes it a unique resource.

Java Deep Learning Cookbook

Author : Rahul Raj
Publisher : Packt Publishing Ltd
ISBN 13 : 1788999479
Total Pages : 294 pages
Book Rating : 4.7/5 (889 download)

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Book Synopsis Java Deep Learning Cookbook by : Rahul Raj

Download or read book Java Deep Learning Cookbook written by Rahul Raj and published by Packt Publishing Ltd. This book was released on 2019-11-08 with total page 294 pages. Available in PDF, EPUB and Kindle. Book excerpt: Use Java and Deeplearning4j to build robust, scalable, and highly accurate AI models from scratch Key FeaturesInstall and configure Deeplearning4j to implement deep learning models from scratchExplore recipes for developing, training, and fine-tuning your neural network models in JavaModel neural networks using datasets containing images, text, and time-series dataBook Description Java is one of the most widely used programming languages in the world. With this book, you will see how to perform deep learning using Deeplearning4j (DL4J) – the most popular Java library for training neural networks efficiently. This book starts by showing you how to install and configure Java and DL4J on your system. You will then gain insights into deep learning basics and use your knowledge to create a deep neural network for binary classification from scratch. As you progress, you will discover how to build a convolutional neural network (CNN) in DL4J, and understand how to construct numeric vectors from text. This deep learning book will also guide you through performing anomaly detection on unsupervised data and help you set up neural networks in distributed systems effectively. In addition to this, you will learn how to import models from Keras and change the configuration in a pre-trained DL4J model. Finally, you will explore benchmarking in DL4J and optimize neural networks for optimal results. By the end of this book, you will have a clear understanding of how you can use DL4J to build robust deep learning applications in Java. What you will learnPerform data normalization and wrangling using DL4JBuild deep neural networks using DL4JImplement CNNs to solve image classification problemsTrain autoencoders to solve anomaly detection problems using DL4JPerform benchmarking and optimization to improve your model's performanceImplement reinforcement learning for real-world use cases using RL4JLeverage the capabilities of DL4J in distributed systemsWho this book is for If you are a data scientist, machine learning developer, or a deep learning enthusiast who wants to implement deep learning models in Java, this book is for you. Basic understanding of Java programming as well as some experience with machine learning and neural networks is required to get the most out of this book.

Cloud Native Security Cookbook

Author : Josh Armitage
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 109810627X
Total Pages : 516 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Cloud Native Security Cookbook by : Josh Armitage

Download or read book Cloud Native Security Cookbook written by Josh Armitage and published by "O'Reilly Media, Inc.". This book was released on 2022-04-21 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: With the rise of the cloud, every aspect of IT has been shaken to its core. The fundamentals for building systems are changing, and although many of the principles that underpin security still ring true, their implementation has become unrecognizable. This practical book provides recipes for AWS, Azure, and GCP to help you enhance the security of your own cloud native systems. Based on his hard-earned experience working with some of the world's biggest enterprises and rapidly iterating startups, consultant Josh Armitage covers the trade-offs that security professionals, developers, and infrastructure gurus need to make when working with different cloud providers. Each recipe discusses these inherent compromises, as well as where clouds have similarities and where they're fundamentally different. Learn how the cloud provides security superior to what was achievable in an on-premises world Understand the principles and mental models that enable you to make optimal trade-offs as part of your solution Learn how to implement existing solutions that are robust and secure, and devise design solutions to new and interesting problems Deal with security challenges and solutions both horizontally and vertically within your business

⬆️ Microsoft Azure AZ-400 (Designing and Implementing Microsoft DevOps Solutions) Practice Tests Exams 347 Questions & Answers PDF

Author : Daniel Danielecki
Publisher : Daniel Danielecki
ISBN 13 :
Total Pages : 210 pages
Book Rating : 4./5 ( download)

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Book Synopsis ⬆️ Microsoft Azure AZ-400 (Designing and Implementing Microsoft DevOps Solutions) Practice Tests Exams 347 Questions & Answers PDF by : Daniel Danielecki

Download or read book ⬆️ Microsoft Azure AZ-400 (Designing and Implementing Microsoft DevOps Solutions) Practice Tests Exams 347 Questions & Answers PDF written by Daniel Danielecki and published by Daniel Danielecki. This book was released on 2024-04-22 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: ⌛️ Short and to the point; why should you buy the PDF with these Practice Tests Exams: 1. Always happy to answer your questions on Google Play Books and outside :) 2. Failed? Please submit a screenshot of your exam result and request a refund; we'll always accept it. 3. Learn about topics, such as: - Agile; - Alerts; - Application Insights; - ASP.NET; - Authentication; - Azure Active Directory (Azure AD); - Azure App Service; - Azure Artifacts; - Azure Automation State Configuration; - Azure Container Registry; - Azure DevOps; - Azure Kubernetes Service (AKS); - Azure Log Analytics; - Azure Monitor; - Azure Pipelines; - Azure Portal; - Azure Repos; - Azure Resource Manager; - Azure SQL Database; - Continuous Integration (CI); - Desired State Configuration (DSC); - Docker; - Git; - GitHub; - Helm; - Java; - Jenkins; - Key Vaults; - Microsoft Teams; - Monitoring; - NuGet; - PowerShell; - Pull Requests; - Service Connections; - Technical Debt; - Virtual Machines (VMs); - WhiteSource Bolt; - Windows Server; - Much More! 4. Questions are similar to the actual exam, without duplications (like in other practice exams ;-)). 5. These tests are not a Microsoft Azure AZ-400 (Designing and Implementing Microsoft DevOps Solutions) Exam Dump. Some people use brain dumps or exam dumps, but that's absurd, which we don't practice. 6. 347 unique questions.

Mastering Databricks Lakehouse Platform

Author : Sagar Lad
Publisher : BPB Publications
ISBN 13 : 9355511396
Total Pages : 359 pages
Book Rating : 4.3/5 (555 download)

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Book Synopsis Mastering Databricks Lakehouse Platform by : Sagar Lad

Download or read book Mastering Databricks Lakehouse Platform written by Sagar Lad and published by BPB Publications. This book was released on 2022-07-11 with total page 359 pages. Available in PDF, EPUB and Kindle. Book excerpt: Enable data and AI workloads with absolute security and scalability KEY FEATURES ● Detailed, step-by-step instructions for every data professional starting a career with data engineering. ● Access to DevOps, Machine Learning, and Analytics wirthin a single unified platform. ● Includes design considerations and security best practices for efficient utilization of Databricks platform. DESCRIPTION Starting with the fundamentals of the databricks lakehouse platform, the book teaches readers on administering various data operations, including Machine Learning, DevOps, Data Warehousing, and BI on the single platform. The subsequent chapters discuss working around data pipelines utilizing the databricks lakehouse platform with data processing and audit quality framework. The book teaches to leverage the Databricks Lakehouse platform to develop delta live tables, streamline ETL/ELT operations, and administer data sharing and orchestration. The book explores how to schedule and manage jobs through the Databricks notebook UI and the Jobs API. The book discusses how to implement DevOps methods on the Databricks Lakehouse platform for data and AI workloads. The book helps readers prepare and process data and standardizes the entire ML lifecycle, right from experimentation to production. The book doesn't just stop here; instead, it teaches how to directly query data lake with your favourite BI tools like Power BI, Tableau, or Qlik. Some of the best industry practices on building data engineering solutions are also demonstrated towards the end of the book. WHAT YOU WILL LEARN ● Acquire capabilities to administer end-to-end Databricks Lakehouse Platform. ● Utilize Flow to deploy and monitor machine learning solutions. ● Gain practical experience with SQL Analytics and connect Tableau, Power BI, and Qlik. ● Configure clusters and automate CI/CD deployment. ● Learn how to use Airflow, Data Factory, Delta Live Tables, Databricks notebook UI, and the Jobs API. WHO THIS BOOK IS FOR This book is for every data professional, including data engineers, ETL developers, DB administrators, Data Scientists, SQL Developers, and BI specialists. You don't need any prior expertise with this platform because the book covers all the basics. TABLE OF CONTENTS 1. Getting started with Databricks Platform 2. Management of Databricks Platform 3. Spark, Databricks, and Building a Data Quality Framework 4. Data Sharing and Orchestration with Databricks 5. Simplified ETL with Delta Live Tables 6. SCD Type 2 Implementation with Delta Lake 7. Machine Learning Model Management with Databricks 8. Continuous Integration and Delivery with Databricks 9. Visualization with Databricks 10. Best Security and Compliance Practices of Databricks

BIG DATA AND HADOOP

Author : Mayank Bhusan
Publisher : BPB Publications
ISBN 13 : 9387284832
Total Pages : 333 pages
Book Rating : 4.3/5 (872 download)

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Book Synopsis BIG DATA AND HADOOP by : Mayank Bhusan

Download or read book BIG DATA AND HADOOP written by Mayank Bhusan and published by BPB Publications. This book was released on 2018-06-02 with total page 333 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains the latest trend in IT industry 'BigData and Hadoop'. It explains how big is 'Big Data' and why everybody is trying to implement this into their IT project.It includes research work on various topics, theoretical and practical approach, each component of the architecture is described along with current industry trends.Big Data and Hadoop have taken together are a new skill as per the industry standards. Readers will get a compact book along with the industry experience and would be a reference to help readers.KEY FEATURES Overview Of Big Data, Basics of Hadoop, Hadoop Distributed File System, HBase, MapReduce, HIVE: The Dataware House Of Hadoop, PIG: The Higher Level Programming Environment, SQOOP: Importing Data From Heterogeneous Sources, Flume, Ozzie, Zookeeper & Big Data Stream Mining, Chapter-wise Questions & Previous Years Questions

Deep Learning with R

Author : François Chollet
Publisher : Simon and Schuster
ISBN 13 : 1638351635
Total Pages : 528 pages
Book Rating : 4.6/5 (383 download)

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Book Synopsis Deep Learning with R by : François Chollet

Download or read book Deep Learning with R written by François Chollet and published by Simon and Schuster. This book was released on 2018-01-22 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Summary Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. The book builds your understanding of deep learning through intuitive explanations and practical examples. Continue your journey into the world of deep learning with Deep Learning with R in Motion, a practical, hands-on video course available exclusively at Manning.com (www.manning.com/livevideo/deep-learning-with-r-in-motion). Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. Deep-learning systems now enable previously impossible smart applications, revolutionizing image recognition and natural-language processing, and identifying complex patterns in data. The Keras deep-learning library provides data scientists and developers working in R a state-of-the-art toolset for tackling deep-learning tasks. About the Book Deep Learning with R introduces the world of deep learning using the powerful Keras library and its R language interface. Initially written for Python as Deep Learning with Python by Keras creator and Google AI researcher François Chollet and adapted for R by RStudio founder J. J. Allaire, this book builds your understanding of deep learning through intuitive explanations and practical examples. You'll practice your new skills with R-based applications in computer vision, natural-language processing, and generative models. What's Inside Deep learning from first principles Setting up your own deep-learning environment Image classification and generation Deep learning for text and sequences About the Reader You'll need intermediate R programming skills. No previous experience with machine learning or deep learning is assumed. About the Authors François Chollet is a deep-learning researcher at Google and the author of the Keras library. J.J. Allaire is the founder of RStudio and the author of the R interfaces to TensorFlow and Keras. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions