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This is a comprehensive list of volunteer computing projects, which are a type of distributed computing where volunteers donate computing time to specific causes. The donated computing power comes from idle CPUs and GPUs in personal computers, video game consoles, [1] and Android devices.
Conferences accepting a broad range of topics from theoretical computer science, including algorithms, data structures, computability, computational complexity, automata theory and formal languages: CCC - Computational Complexity Conference; FCT – International Symposium on Fundamentals of Computation Theory
The term "data science" has been traced back to 1974, when Peter Naur proposed it as an alternative name to computer science. [6] In 1996, the International Federation of Classification Societies became the first conference to specifically feature data science as a topic. [6] However, the definition was still in flux.
Social data science is an interdisciplinary field that addresses social science problems by applying or designing computational and digital methods.As the name implies, Social Data Science is located primarily within the social science, but it relies on technical advances in fields like data science, network science, and computer science.
The goals of the project are to build a community of interest around computer science, and to provide a focal point for coordinating efforts to improve Wikipedia's computer science articles. The scope of the project includes all articles in the area of computer science , including computer programming and software engineering .
Data science process flowchart from Doing Data Science, by Schutt & O'Neil (2013) Analysis refers to dividing a whole into its separate components for individual examination. [ 10 ] Data analysis is a process for obtaining raw data , and subsequently converting it into information useful for decision-making by users. [ 1 ]
Spatial data mining is the application of data mining methods to spatial data. The end objective of spatial data mining is to find patterns in data with respect to geography. So far, data mining and Geographic Information Systems (GIS) have existed as two separate technologies, each with its own methods, traditions, and approaches to ...
The significantly reorganized revised edition of the book (2023) [2] expands and modernizes the presented mathematical principles, computational methods, data science techniques, model-based machine learning and model-free artificial intelligence algorithms. The 14 chapters of the new edition start with an introduction and progressively build ...