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TunedIT - Data mining & machine learning data sets, algorithms, challenges | tunedit.org Reviews
https://tunedit.org
Platform for sharing and evaluation of intelligent algorithms. Data mining data, experiments, datasets, performance analysis, data repository, challenges. Research and applications, prediction. Data mining and machine learning
TunedIT Data Mining Blog | Data mining, machine learning, artificial intelligence. Research and applications
TunedIT Data Mining Blog. Data mining, machine learning, artificial intelligence. Research and applications. Winner’s notes. Eleftherios Spyromitros – Xioufis on Music Instruments Recognition. July 20, 2011. By Eleftherios Spyromitros Xioufis (lefman), winner of the Music Instruments. Track of ISMIS 2011 Contest: Music Information Retrieval. I am currently in the 1st year of my PhD studies in the Department of Informatics of the Aristotle University of Thessaloniki. The single instruments training set co...
TunedIT Wiki Index - TunedIT Wiki
Data Mining, Machine Learning, Artificial Intelligence. Is a research and competition platform for Data Mining, Machine Learning and Artificial Intelligence. You will find here all documentation of the system. FAQ - Launching a Challenge. FAQ - Industrial Challenges. View and post questions and answers. Follow us to receive all the freshest news. In case you want to reference TunedIT in a publication. To report a bug. Or suggest a new feature. Please send us an e-mail:. Powered by Wikidot.com. Wikidot...
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Data Mining Competitions | TunedIT
http://www.tunedit.org/data-competitions
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. Is the first web platform for hosting data mining competitions, launched in 2009 on top of the Research. Framework for the evaluation of data-driven algorithms. TunedIT Challenges provide extremely flexible and easy way to launch data mining contests of any type, in every application domain. Thanks to live Leaderboard, competitions are interactive. No more boring assignments! Tutors may launch online...
ISMIS 2011 Contest: Music Information Retrieval | TunedIT
http://www.tunedit.org/challenge/music-retrieval
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. ISMIS 2011 Contest: Music Information Retrieval. The challenge is over now. Click here to view the Summary. Data mining contest associated with the 19th International Symposium on Methodologies for Intelligent Systems (ISMIS 2011). The contest comprises 2 tracks:. Recognition of genre of music (jazz, rock, pop, .) from a short sample. Recognition of instruments playing together in a given sample.
Task - ISMIS 2011 Contest: Music Information Retrieval - Instruments | TunedIT
http://www.tunedit.org/challenge/music-retrieval/instruments
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. ISMIS 2011 Contest: Music Information Retrieval. It is fairly easy to automatically recognize single instruments. However, when more than one instrument plays at the same time, the task becomes much more difficult. In this track, the goal is to build a model based on data collected for both single instruments and example mixtures in order to recognize pairs of instruments. MFCC1-13 - MFCC coefficients.
IEEE ICDM Contest: TomTom Traffic Prediction for Intelligent GPS Navigation | TunedIT
http://www.tunedit.org/challenge/IEEE-ICDM-2010
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. IEEE ICDM Contest: TomTom Traffic Prediction for Intelligent GPS Navigation. The challenge is over now. Click here to view the Summary. Data mining competition being a part of IEEE International Conference on Data Mining 2010. ICDM), Sydney, Australia, Dec 14-17. Sponsored by TomTom. Held under the patronage of the President of Warsaw, Mrs. Hanna Gronkiewicz-Waltz. There are 3 tasks:. Traffic congest...
Task - ISMIS 2011 Contest: Music Information Retrieval - Genres | TunedIT
http://www.tunedit.org/challenge/music-retrieval/genres
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. ISMIS 2011 Contest: Music Information Retrieval. The feature vector consists of 191 parameters, the first 127 parameters are based on the MPEG-7 standard, the remaining ones are cepstral coefficients descriptors and time-related dedicated parameters:. A) parameter 1: Temporal Centroid,. B) parameter 2: Spectral Centroid average value,. C) parameter 3: Spectral Centroid variance,. L) parameters 103-12...
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Organizer's Guide - TunedIT Wiki
http://wiki.tunedit.org/doc:challenges-organizer-guide
Data Mining, Machine Learning, Artificial Intelligence. Raquo; Organizer's Guide. For a brief overview of challenge organization, see Quick Tutorial. What is a Challenge? Publishing, Opening and Closing. What is a Challenge? Is an on-line data mining competition run on TunedIT website. It can be launched. By any registered user of TunedIT - the. Timetable and rules of participation. After. The challenge, users of TunedIT may register as. Evaluated afterwards by the organizer using TunedTester. Thus, ther...
How To Cite - TunedIT Wiki
http://wiki.tunedit.org/doc:how-to-cite
Data Mining, Machine Learning, Artificial Intelligence. If you wish to reference TunedIT in a publication, please cite the following paper. Wojnarski, M., Stawicki, S. and Wojnarowski, P. TunedIT.org: System for Automated Evaluation of Algorithms in Repeatable Experiments. Rough Sets and Current Trends in Computing (RSCTC), 2010, LNAI vol. 6086, 20-29, Springer. Powered by Wikidot.com. Click here to edit contents of this page. Append content without editing the whole page source. Notify administrators if...
Launching a challenge - Tutorial - TunedIT Wiki
http://wiki.tunedit.org/doc:challenges-tutorial
Data Mining, Machine Learning, Artificial Intelligence. Launching a challenge - Tutorial. Raquo; Launching a challenge - Tutorial. 1 Create an empty challenge. Go to New Challenge. Page Provide basic information (can be changed later on):. Title - human-readable title to appear on the competition pages. Name - machine-readable name that will be used to create URL address of contest pages. Folder - where in Repository you'd like to store contest files: datasets, solutions, supplemental materials. There ar...
Launching a Challenge - FAQ - TunedIT Wiki
http://wiki.tunedit.org/launch-challenge-faq
Data Mining, Machine Learning, Artificial Intelligence. Launching a Challenge - FAQ. For a comprehensive manual of challenge organization see: Organizer's Guide. Who can start a challenge and for what purpose? Can be launched by:. Of laboratory classes - To organize assignment task in a form of a contest, to make it more attractive and valuable for students, and to avoid manual marking of assignments. In a company. Team of researchers. Can be launched by:. To engage scientific community in investigation ...
TunedIT Challenges - TunedIT Wiki
http://wiki.tunedit.org/doc:challenges
Data Mining, Machine Learning, Artificial Intelligence. FAQ - Launching a Challenge. FAQ - Industrial Challenges. Powered by Wikidot.com. Click here to edit contents of this page. Click here to toggle editing of individual sections of the page (if possible). Watch headings for an edit link when available. Append content without editing the whole page source. Check out how this page has evolved in the past. If you want to discuss contents of this page - this is the easiest way to do it.
About TunedIT Wiki - TunedIT Wiki
http://wiki.tunedit.org/about
Data Mining, Machine Learning, Artificial Intelligence. Raquo; About TunedIT Wiki. Wikitunedit.org) is a documentation site of TunedIT. The research and competition platform for scientists, practitioners and programmers working in the areas of Data Mining, Machine Learning, Artificial Intelligence and related. To learn more about TunedIT go to http:/ tunedit.org. Powered by Wikidot.com. Click here to edit contents of this page. Append content without editing the whole page source. Find out what you can do.
Industrial Challenges - FAQ - TunedIT Wiki
http://wiki.tunedit.org/industrial-faq
Data Mining, Machine Learning, Artificial Intelligence. Industrial Challenges - FAQ. How many people participate in a challenge? Why so many people participate if only few of them receive awards and the rest get nothing? Who are the participants? Are they skilled enough to come up with valuable solutions? How long does it take: challenge itself and its configuration? How much does it cost? Why to launch a contest if I can hire an employee instead? How many people participate in a challenge? To have FUN&#...
TunedIT Wiki Index - TunedIT Wiki
http://wiki.tunedit.org/start
Data Mining, Machine Learning, Artificial Intelligence. Is a research and competition platform for Data Mining, Machine Learning and Artificial Intelligence. You will find here all documentation of the system. FAQ - Launching a Challenge. FAQ - Industrial Challenges. View and post questions and answers. Follow us to receive all the freshest news. In case you want to reference TunedIT in a publication. To report a bug. Or suggest a new feature. Please send us an e-mail:. Powered by Wikidot.com. Wikidot...
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Tuned In With Corinne
Tuned In With Corinne. CONTACT: Corinne.Henneberry@gmail.com. VH1 Buzz Promo Video. Nick Cannon Never Stops Working! SwizzBeatz Gives Back….
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TunedIT - Data mining & machine learning data sets, algorithms, challenges
Machine Learning and Data Mining Algorithms. Automated Tests, Repeatable Experiments, Meaningful Results. Reproducibility of experiments is the cornerstone of science. TunedIT is the first research platform which enables automation of data mining experiments and generation of reproducible results that can be easily shared with others and verified. Or internal assignment for your students. Need an Intelligent Algorithm? Companies that seek dedicated data mining algorithms or predictive models may post a r...
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Chose a type of music on the left! To play the media you will need to either update your browser to a recent version or update your Flash plugin. Sueno Latino (Paradise remix). Johnny And Mary (feat. Bryan Ferry). You can fuck off. We Gonna Make It (Alan Braxe Mix). Blackwater (Strings Vocal Mix). I Want To Thank You (Earl Jeffers Edit). To get the best of Tunediving, follow us on facebook.
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BRIDE VERTEX Collaboration sheet. Please contact sales@tunedjapan.com. Interview with M. Suzuki. more. TunedJapan has been an authorized dealer Bee-R products since January 2015. This video. more. Interview with Mr. Morishita. more. The Little Engine That Could. Interview with D. Mendoza from SsAuto Power. more. Fortune Favors the Brave! I thank all of you. I thank all of you. Privacy and Security Polices.
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Forum tuningowe ekipy z okolic Gogolina i Krapkowic. Nie jesteś zalogowany na forum. Okazja dnia w RTV EURO AGD. Sprawdź! 2015-07-29 23:32:24 przez Paco. W tytule pisać [k] [s] lub [o]. Ciekawe ogłoszenia z innych portali. Liczba użytkowników, którzy odwiedzili dzisiaj forum: 0. Najwięcej użytkowników online (5) było 2015-06-17 13:55:56. Ciekawe ogłoszenia z innych portali. Atom - aktywne wątki. Forum oparte na FluxBB.
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