Han Hee-sun: Building Big Data for AI Analysis

This book is built by the process of refining, converting and re-recognising and testing data to achieve its goal of collecting and storing data. The scheme to see the original document is the following image:. The following steps are important: (1) Collecting and storing data, including non-symbol and formal MSS data, and in the storage, storing data on the MSFS and Hbase. [gasps]. "The Internet is a new world. (2) Pre-handling checks out the user's user's data, or a user', for example, for a detailed list of the original data load. [gasps]. What do we do with one big data, mon 2. R to the Big Data Act. (3) The refining process will essentially identify the data required for analysis to build analytical data sets, and will do the processing and error-clerification of the data. [sighs]. Convert to a suitable analysis, Don 7. (Data Browser). (4) Convert / Reconciliation and harvests include refined data in a form that is easy to analyze with Big Data. The conversion technique includes flatening, counting, generalization, formalization and the production of derivatives. [Applause]. See the various types of data loading, the derivative of the end 5 and the derivatives of the last seven data browsing for the next one.

Korean title: AI 분석을 위한 빅데이터 구축

Korean author: 한희선

Korean publisher: 구민사

ISBN-13: 9791158138479