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MAASDATA 2019 : 12th MAASTRICHT SCHOOL ON DATA SCIENCE | |||||||||||
Link: https://project.dke.maastrichtuniversity.nl/datamining/ | |||||||||||
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Call For Papers | |||||||||||
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** ** ** 12th MAASTRICHT SCHOOL ON DATA SCIENCE, ** ** Department of Data Science and Knowledge Engineering ** ** Maastricht University, ** ** Maastricht, The Netherlands ** ** ** ** June 26 - June 28, 2019 ** ** ** ** https://project.dke.maastrichtuniversity.nl/datamining/ ** ** ** ** Apologies if you receive multiple copies of this announcement ** ** Please forward to anyone who might be interested ** ** ** ********************************************************************* School on Data Science An intensive 3-day introduction to methods and applications of data science Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands June 26 - June 28, 2019 Introduction With the promises of Data Science, modern organisations collect terabytes of data related to their function, market share, business activities, and daily operation. Usually the data collected provides only a low level view of the "facts and figures", and Data Science can help to translate this data into knowledge that can be used to understand and eventually improve the overall performance of the organisations. Data Science employes techniques from statistics, machine learning, artificial intelligence, and computer science. It has been successfully applied in many domains including Business, Medicine, Biology, Economics, Military, etc. As a result, most organisations are starting to recognise their need for data scientists specialists, and this is where this school can be of help. Description Our school on data science balances both theory and practice. We think it is important to not only learn to use the available techniques, but to also apply them correctly and when appropriate. Each lecture is accompanied by a lab in which participants experiment with the techniques introduced in the lecture. A number of real data sets will be analysed and discussed. Throughout the duration of the school participants develop their own abilities to safely and reliably apply data-science techniques for business and research purposes. Content The school will cover the topics listed below. - Knowledge Discovery Process + Data Collection and Preparation + Feature Selection: Filters, Wrappers, Embedded Methods - Machine Learning Techniques: + Regression: Linear Regression, Ridge Regression, LASSO, Nearest Neighbor Regression, Regression Trees, Model Trees + Classification: Logistic Regression, Support Vector Machines, Decision Trees, Decision Rules, Nearest Neighbor Classification + Clustering: k-means, hierarchical clustering, DBSCAN, and validation + Association rules: Apriori, frequent item mining, rule generation + Deep Learning: Classical Feedforward Neural Nets, Convolutional Neural Networks, Regularization, Recurrent Neural Networks, and GANs - Model Validation: Hold-out Validation, Cross Validation, ROC Analysis etc. Intended Audience: This school is intended for four groups of data-science beginners: students, scientists, engineers, and experts in specific fields who need to apply data- science techniques to their scientific research, business management, or other related applications. Prerequisites: No special knowledge in statistics, artificial intelligence, or machine learning is required. An affinity with science is sufficient as is a high degree of enthusiasm for new scientific approaches. Registration: To register for the school please send an email to: smirnov@maastrichtuniversity.nl kurt.driessens@maastrichtuniversity.nl (Please send the registration to both e-mails) In the e-mail please specify: your name, university/organisation, address, phone, e-mail Registration Deadline: June 24, 2019 Registration fees: Academic fee 840 Euros Non-academic fee 1680 Euros (to be paid after the School) Contact: Evgueni Smirnov and Kurt Driessens Department of Data Science and Knowledge Engineering Faculty of Humanities and Sciences Maastricht University P.O.Box 616 6200 MD Maastricht The Netherlands Phone: +31 (0) 43 38 82023 Fax: +31 (0) 43 38 84897 E-mails: smirnov@maastrichtuniversity.nl kurt.driessens@maastrichtuniversity.nl |
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