Kindle Cloud Reader的問題，透過圖書和論文來找解法和答案更準確安心。 我們找到下列懶人包和總整理

Data Analysis with Python and Pyspark

為了解決Kindle Cloud Reader的問題，作者Rioux, Jonathan 這樣論述：

Think big about your data! PySpark brings the powerful Spark big data processing engine to the Python ecosystem, letting you seamlessly scale up your data tasks and create lightning-fast pipelines.In Data Analysis with Python and PySpark you will learn how to: Manage your data as it scales acros

s multiple machines Scale up your data programs with full confidence Read and write data to and from a variety of sources and formats Deal with messy data with PySpark’s data manipulation functionality Discover new data sets and perform exploratory data analysis Build automated data pipelines that t

ransform, summarize, and get insights from data Troubleshoot common PySpark errors Creating reliable long-running jobs Data Analysis with Python and PySpark is your guide to delivering successful Python-driven data projects. Packed with relevant examples and essential techniques, this practical book

teaches you to build pipelines for reporting, machine learning, and other data-centric tasks. Quick exercises in every chapter help you practice what you’ve learned, and rapidly start implementing PySpark into your data systems. No previous knowledge of Spark is required. Purchase of the print boo

k includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology The Spark data processing engine is an amazing analytics factory: raw data comes in, insight comes out. PySpark wraps Spark’s core engine with a Python-based API. It helps simplify Spark’s steep

learning curve and makes this powerful tool available to anyone working in the Python data ecosystem. About the bookData Analysis with Python and PySpark helps you solve the daily challenges of data science with PySpark. You’ll learn how to scale your processing capabilities across multiple machin

es while ingesting data from any source--whether that’s Hadoop clusters, cloud data storage, or local data files. Once you’ve covered the fundamentals, you’ll explore the full versatility of PySpark by building machine learning pipelines, and blending Python, pandas, and PySpark code. What’s inside

Organizing your PySpark code Managing your data, no matter the size Scale up your data programs with full confidence Troubleshooting common data pipeline problems Creating reliable long-running jobs About the reader Written for data scientists and data engineers comfortable with Python. About th

e author As a ML director for a data-driven software company, Jonathan Rioux uses PySpark daily. He teaches the software to data scientists, engineers, and data-savvy business analysts. Table of Contents 1 Introduction PART 1 GET ACQUAINTED: FIRST STEPS IN PYSPARK 2 Your first data program in PySp

ark 3 Submitting and scaling your first PySpark program 4 Analyzing tabular data with pyspark.sql 5 Data frame gymnastics: Joining and grouping PART 2 GET PROFICIENT: TRANSLATE YOUR IDEAS INTO CODE 6 Multidimensional data frames: Using PySpark with JSON data 7 Bilingual PySpark: Blending Python and

SQL code 8 Extending PySpark with Python: RDD and UDFs 9 Big data is just a lot of small data: Using pandas UDFs 10 Your data under a different lens: Window functions 11 Faster PySpark: Understanding Spark’s query planning PART 3 GET CONFIDENT: USING MACHINE LEARNING WITH PYSPARK 12 Setting the stag

e: Preparing features for machine learning 13 Robust machine learning with ML Pipelines 14 Building custom ML transformers and estimators

Kindle Cloud Reader進入發燒排行的影片

探討以紙本內容轉製數位出版品之研究

為了解決Kindle Cloud Reader的問題，作者丁永照 這樣論述：

數位出版起源可推到2000年網際網路興起的時候，當時有科技業者提出數位出版的概念，就是利用網頁在螢幕上作閱讀，但當時螢幕閱讀體驗不佳並未形成趨勢。美國的電子書產業自2007年亞馬遜推出Kindle開始快速發展，同年第一代iPhone發表引領起的智能手機快速普及全世界，2010年賈伯斯在蘋果公司發佈iPad後，讓數位出版結合了智能載具，掀起另一波數位閱讀的風潮。1991至2015年間相關論文，25年探討電子書相關學術論文之成長趨勢與現況指出，電子書內容研究多為設計書籍，相關論文過少，舉電子書定價或版面設計題目為例，本研究研究者進入數位出版業至今，搜尋到許多論文提出是對電子書定價模式探討、閱聽者

行為模式研究、閱讀器介面之字體字級或版面編排瀏覽設計等，隨著時間推衍或許會有新的模式或新的問題產生，但每位學者對相似主題卻往往提出不同的看法，例如定價策略雖有許多研究者下結論、提出建議與出不同的成果，但產業界經過這麼多年仍然還在探討電子書定價模式，這是否表現出學術研究的不統一？這廿多年鮮有業界的經驗提出紙本轉型數位的研究，一般是業界經驗座談，或是特定數位出版軟體教學。本研究的範圍以台灣繁體中文圖書出版為主，轉型數位出版的方式也不限於工具與載具，期望可以給出版業想轉型數位出版，或是有紙本內容的政府單位想轉型進入數位出版時的重要參考依據。本研究將文本分析結果以及專家訪談的結果綜合出，將原本紙本內容

碎片化是目前數位出版的趨勢，碎片化的過程其實各有不同，從紙本轉製數位出版品的過程也是將資料碎片化的方式之一，碎片化的資料以元件的方式有系統的存放在雲端資料庫中，那麼整個數位出版的形式有很不一樣的呈現，不再以形式或是檔案格式所侷限，而是依照需求來給予不同的格式，如同專家所說：無論平台或是其他數位需求的格式，內容已經準好了，隨時可用，商業模式也可據此產生，IP經濟就是在此行況下新的經濟模式。

ASP.NET Core in Action

為了解決Kindle Cloud Reader的問題，作者Lock, Andrew 這樣論述：

Summary ASP.NET Core in Action is for C# developers without any web development experience who want to get started and productive fast using ASP.NET Core 2.0 to build web applications. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About

the Technology The dev world has permanently embraced open platforms with flexible tooling, and ASP.NET Core has changed with it. This free, open source web framework delivers choice without compromise. You can enjoy the benefits of a mature, well-supported stack and the freedom to develop and depl

oy from and onto any cloud or on-prem platform. About the Book ASP.NET Core in Action opens up the world of cross-platform web development with .NET. You'll start with a crash course in .NET Core, immediately cutting the cord between ASP.NET and Windows. Then, you'll begin to build amazing web appli

cations step by step, systematically adding essential features like logins, configuration, dependency injection, and custom components. Along the way, you'll mix in important process steps like testing, multiplatform deployment, and security. What's InsideCovers ASP.NET Core 2.0Dynamic page generati

on with the Razor templating engineDeveloping ASP.NET Core apps for non-Windows serversClear, annotated examples in C#About the Reader Readers need intermediate experience with C# or a similar language. About the Author Andrew Lock has been developing professionally with ASP.NET for the last seven y

ears. His focus is currently on the ASP.NET Core framework. Table of Contents PART 1 - GETTING STARTED WITH MVCGetting started with ASP.NET CoreYour first applicationHandling requests with the middleware pipelineCreating web pages with MVC controllersMapping URLs to methods using conventional routin

gThe binding model: retrieving and validating user inputRendering HTML using Razor viewsBuilding forms with Tag HelpersCreating a Web API for mobile and client applications using MVCP PART 2 - BUILDING COMPLETE APPLICATIONSService configuration with dependency injectionConfiguring an ASP.NET Core ap

plicationSaving data with Entity Framework CoreThe MVC filter pipelineAuthentication: adding users to your application with IdentityAuthorization: securing your applicationPublishing and deploying your applicationPART 3 - EXTENDING YOUR APPLICATIONSMonitoring and troubleshooting errors with loggingI

mproving your application's securityBuilding custom componentsTesting your application Andrew Lock graduated with an Engineering degree from Cambridge University, specializing in Software Engineering, and went on to obtain a PhD in Digital Image Processing. He has been developing professionally wi

th .NET for the last 7 years. His focus is currently on the new ASP.NET Core framework.

以區塊鏈為基礎建置電子書數位版權管理模型

為了解決Kindle Cloud Reader的問題，作者蔡正一 這樣論述：

近20年來，隨著行動通訊技術的快速發展，以及智慧型手機與平板電腦的普及化，徹底改變了人類的日常生活習慣及獲取資訊之方式。從過去閱讀紙本書籍或報紙，轉變為閱讀電子檔案或網路新聞，電子書籍需求量與日俱增，使得傳統出版業者，面臨了巨大的衝擊與挑戰。雖然數位出版的成本較為低廉，但容易被有心人士複製並快速散播，造成出版商及作者的損失，因此如何有效的管理電子書籍的數位版權，成為一個重要的議題。本研究文針對電子書籍版權管理議題，提出一個以區塊鏈為基礎的管理模式，利用區塊鏈技術中，特有的去中心化、不可竄改、以及資料透明公開等特性，將電子書從出版、發行、銷售到轉移，整個資料完整記錄於電子書區塊鏈網路中，任何一

位作者、出版商或是消費者，都可以透過電子書區塊鏈網路，對於所購買或是持有的電子書，進行數位版權的確認，作者以及出版商也可以透過電子書區塊鏈網路，查詢實際發行流通的電子書數量，協助改善整體電子書的數位版權管理。