- Using various data mining techniques and technologies, the company collects and stores materials to provide data analysis and reporting.
- Business intelligence systems provide a fast and convenient way to store data, enabling companies to make better business decisions.
- Key benefits include understanding large volumes of transaction data (OLTP), data integration, fast response to decisions, strong analytical capabilities, and improving customer satisfaction.
- Using various data mining techniques and technologies, the company collects and stores materials to provide data analysis and reporting.
- Business intelligence systems provide a fast and convenient way to store data, enabling companies to make better business decisions.
- Key benefits include understanding large volumes of transaction data (OLTP), data integration, fast response to decisions, strong analytical capabilities, and improving customer satisfaction.
This document contains a GET request for invoices between two dates. The response includes two invoices with details like ID, date, title, and amount. Ellipses indicate additional invoices are included in the full response.
This document provides an introduction to exploring and visualizing data using the R programming language. It discusses the history and development of R, introduces key R packages like tidyverse and ggplot2 for data analysis and visualization, and provides examples of reading data, examining data structures, and creating basic plots and histograms. It also demonstrates more advanced ggplot2 concepts like faceting, mapping variables to aesthetics, using different geoms, and combining multiple geoms in a single plot.
This document discusses applying data mining techniques to analyze active users on Reddit. It defines active users as those who posted or commented in at least 5 subreddits and have at least 5 posts/comments in each subreddit. The preprocessing steps extract over 25,000 active users and their posts from the raw Reddit data. K-means clustering is then used to cluster the active users into 10 groups based on their activities to gain insights into different types of active users on Reddit.
在這資料科學逐漸成為顯學的年代,無論面對的是資料的幾個 V,其中最重要的永遠都是 Value (價值) 這個 V,而資料探勘正是一種透過系統化的方式釐清資料的脈絡、找出其中有價值的特徵與相關性的技術。這門六小時的課程,將從最實務的角度切入,與大家分享如何將現實中極待解決的問題,轉換成可以利用資料探勘技術處理的問題,並且運用 R 語言中各種強大的工具,進行關聯性分析、迴歸分析以及叢聚分析,以達成將資料中隱藏的資訊挖掘出來的最終目標。
在此課程中將帶領對資料分析感到陌生卻又充滿興趣的您,完整地學會運用 R 語言從最初的蒐集資料、探索性分析解讀資料,並進行文字探勘,發現那些肉眼看不見、隱藏在資料底下的意義。此課程主要設計給對於 R 語言有基本認識,想要進一步熟悉實作分析的朋友們,希望在課程結束後,您能夠更熟悉 R 語言這個豐富的分析工具。透過蘋果日報慈善捐款的資料集,了解如何從頭解析網頁,撰寫爬蟲自動化收集資訊;取得資料後,能夠靈活處理資料,做清洗、整合及探索;並利用現成的套件進行文字探勘、文本解析;我們將一步步實際走一回資料分析的歷程,處理、觀察、解構資料,試著看看人們在捐款的決策過程中,究竟是什麼因素產生了影響,以及這些結果又是如何從資料中挖掘而出的呢?
Jackson Hung - 轉換人生實踐者
活到現在,我們總在讀書,卻很少思考,更少為自己行動,因為代價太多。即使嘗試改變生活的一小塊,又難以理直氣壯面對眼光、及自我內心的懷疑。很幸運,15歲被丟到中美洲,再去美國念大學,又被騙回台灣工作。被逼得成長 。但探索人生的過程中,雖有勇氣數次轉換領域,從生化、專案、智財、金融交易、到程式。可是"Out of Comfortable"只是一個跨步,不是路程。最後,我創業了。希望能分享,這條不斷挑戰自我、有徬徨有懷疑的路怎麼走出來的!