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Data Mining Community's Top Resource

Data Mining Community's Top Resource
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ACM KDD CUP Skip to Main Content Area Home » Awards » KDD Cup KDD Cup is the annual Data Mining and Knowledge Discovery competition organized by ACM Special Interest Group on Knowledge Discovery and Data Mining, the leading professional organization of data miners. Below are links to the descriptions of all past tasks. KDD Cup 2010: Student performance evaluation KDD Cup 2009: Customer relationship prediction KDD Cup 2008: Breast cancer KDD Cup 2007: Consumer recommendations KDD Cup 2006: Pulmonary embolisms detection from image data KDD Cup 2005: Internet user search query categorization KDD Cup 2004: Particle physics; plus protein homology prediction KDD Cup 2003: Network mining and usage log analysis KDD Cup 2002: BioMed document; plus gene role classification KDD Cup 2001: Molecular bioactivity; plus protein locale prediction KDD Cup 2000: Online retailer website clickstream analysis KDD Cup 1999: Computer network intrusion detection KDD Cup 1998: Direct marketing for profit optimization Latest Resources

Freebase SEASR FlowingData | Data Visualization and Statistics Pattern Pattern is a web mining module for the Python programming language. It has tools for data mining (Google, Twitter and Wikipedia API, a web crawler, a HTML DOM parser), natural language processing (part-of-speech taggers, n-gram search, sentiment analysis, WordNet), machine learning (vector space model, clustering, SVM), network analysis and <canvas> visualization. The module is free, well-document and bundled with 50+ examples and 350+ unit tests. Download Installation Pattern is written for Python 2.5+ (no support for Python 3 yet). To install Pattern so that the module is available in all Python scripts, from the command line do: > cd pattern-2.6 > python setup.py install If you have pip, you can automatically download and install from the PyPi repository: If none of the above works, you can make Python aware of the module in three ways: Quick overview pattern.web pattern.en The pattern.en module is a natural language processing (NLP) toolkit for English. pattern.search pattern.vector Case studies

Медико-экологический атлас Воронежской области: Об атласе Essential Resources: Mapping applications, frameworks and libraries This is part of a series of posts to share with readers a useful collection of some of the most important, effective and practical data visualisation resources. This post presents the many different options for visualisation spacial data. Please note, I may not have personally used all the packages or tools presented but have seen sufficient evidence of their value from other sources. Whilst some inclusions may be contentious from a quality/best-practice perspective, they may still provide some good features and provide value to a certain audience out there. Finally, to avoid re-inventing the wheel, descriptive text may have been reproduced from the native websites if they provide the most articulate descriptions. ArcGIS ArcGIS is a range of powerful and versatile mapping tools from ESRI. Examples/references: ArcGIS Desktop, ArcGIS Web Mapping, ArcGIS Explorer, Gallery GeoCommons Examples/references: GeoIQ, User Manual Indiemapper InstantAtlas Target Map Examples/references: Blog/Help CartoDB

38 Tools For Beautiful Data Visualisations | DBi As we enter the Big Data era, it becomes more important to properly expand our capacity to process information for analysis and communication purposes. In a business context, this is evident as good visualisation techniques can support statistical treatment of data, or even become an analysis technique. But also, can be used as a communication tool to report insights that inform decisions. Today there are plenty of tools out there that can be used to improve your data visualisation efforts at every level. Below we list a non-exhaustive list of resources. Javascript Libraries Circular Hierarchy – D3.js Python Libraries Kartograph.py – Mapsigraph – Node-link, treesMatplotlib – Most types of statistical plotsPycha – Pie chart, bar chart, area chartNetworkX – Node-link Java / PHP Web Applications TileMill – Running Map Programming Languages Hyperbolic Tree – NYTimes 365/360 Generated with Processing Desktop Applications Treemap – Tableau

Internet Archive: Digital Library of Free Books, Movies, Music & Wayback Machine Домашнее задание от МТИ: пишем нейросеть для манёвров в дорожном трафике / Geektimes DeepTraffic — интересная интерактивная игра, поучаствовать в которой может любой желающий, а студенты Массачусетского технологического института (МТИ), которые изучают курс глубинного обучения в беспилотных автомобилях, обязаны показать хороший результат в этой игре, чтобы им засчитали выполненное задание. Участникам предлагают спроектировать агента ИИ, а именно, спроектировать и обучить нейронную сеть, которая покажет себя лучше конкурентов в плотном дорожном потоке. В управление агенту даётся один автомобиль (красного цвета). Он должен научиться маневрировать в потоке наиболее эффективным способом. По условиям игры, в автомобиль изначально встроена система безопасности, то есть он не сможет врезаться или улететь с дороги. Изначально предлагается базовый код агента, который можно модифицировать прямо в игровом окне — и сразу запускать на исполнение, то есть на обучение нейросети. Базовый код Разные режимы Road Overlay позволяют понять, как работает и обучается нейросеть.

Freedom of Information Act Electronic Reading Room | CIA FOIA (foia.cia.gov) President's Daily Brief 1969-1977 The declassified President’s Daily Briefs (PDBs) from the Nixon and Ford presidential administrations in this collection include about 2,500 documents and 28,000 pages. As part of this release, CIA held a symposium, "The President's Daily Brief: Delivering Intelligence to Nixon and Ford, " at the Richard Nixon Presidential Library in Yorba Linda, CA on 24 August 2016. 31 October 2016 - Release of Draft Fifth Volume, CIA's Internal Investigation of the Bay of Pigs Between 1979 and 1984, Central Intelligence Agency (CIA) staff historian Jack Pfeiffer prepared five volumes of the Agency’s Official History of the Bay of Pigs Operation.

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