The document discusses spatial data and its applications. It describes how spatial data is produced through remote sensing from satellites and aerial photography. It then discusses various applications of spatial data in public sector planning, natural resource management, and enterprise spatial analysis. The document also introduces the concept of geo-internet of things (geo-IOT) and potential applications that combine spatial data and IOT.
The document summarizes Eddie Lin's work in data science for social good. It discusses his participation in the 2016 Data Science for Social Good Summer Fellowship at the University of Chicago, and his current work at DSaPP, which uses data and machine learning to help solve social problems. It outlines common machine learning tasks and how they are similar to concepts learned in kindergarten. It also describes typical social good project categories and emphasizes open source tools.
有人用勞力做公益,也有人用財力做公益,如果用資料力來做公益,不知道會擦出怎樣的火花?
2015年,我們打造一個「資料力,做公益」的交流與媒合平台,稱為「D4SG 計畫」 (Data for Social Good)。透過社群、黑客松、資料競賽、長期專案...等方式推動資料人與非營利組織的深度交流。這場演講將從資料人的角度分享如何與NPO/NGO合作,把冰冷的資料轉換化成有溫度的故事。
The document summarizes an emergency data analysis challenge presentation by Lee Shao-Fan and Yang Cheng-Han. It includes an outline, exploratory data analysis of emergency numbers over time by hospital level and individual hospitals, and a discussion of model building to predict total emergency numbers based on time, hospital, patient-doctor ratios and other factors for both hospital levels 1 and 2. Strange phenomena were noted in the emergency numbers for one hospital. Models were developed separately for hospital levels 1 and 2 to account for their differences.
The document discusses point clouds and how they are used. A point cloud is a large set of data points that represent a 3D object or environment. Point clouds can be created from laser scanners, cameras, sonar and other sensors. They provide a precise 3D representation of surfaces and are used in applications such as archaeology, mapping, self-driving cars, and more. The use of point clouds is growing across many industries as a way to efficiently capture 3D spatial data.
有人用勞力做公益,也有人用財力做公益,如果用資料力來做公益,不知道會擦出怎樣的火花?
2015年,我們打造一個「資料力,做公益」的交流與媒合平台,稱為「D4SG 計畫」 (Data for Social Good)。透過社群、黑客松、資料競賽、長期專案...等方式推動資料人與非營利組織的深度交流。這場演講將從資料人的角度分享如何與NPO/NGO合作,把冰冷的資料轉換化成有溫度的故事。
The document summarizes an emergency data analysis challenge presentation by Lee Shao-Fan and Yang Cheng-Han. It includes an outline, exploratory data analysis of emergency numbers over time by hospital level and individual hospitals, and a discussion of model building to predict total emergency numbers based on time, hospital, patient-doctor ratios and other factors for both hospital levels 1 and 2. Strange phenomena were noted in the emergency numbers for one hospital. Models were developed separately for hospital levels 1 and 2 to account for their differences.
The document discusses point clouds and how they are used. A point cloud is a large set of data points that represent a 3D object or environment. Point clouds can be created from laser scanners, cameras, sonar and other sensors. They provide a precise 3D representation of surfaces and are used in applications such as archaeology, mapping, self-driving cars, and more. The use of point clouds is growing across many industries as a way to efficiently capture 3D spatial data.