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DTSTAMP:20260717T133122Z
UID:1cebac51-66b1-411f-a406-95b72183c49e
DTSTART:20220119T080000Z
DTEND:20220121T160000Z
DESCRIPTION:The purpose of this course is to present researchers and scient
 ists with R implementation of Machine Learning methods. The first part of 
 the course will consist of introductory lectures on popular Machine Learni
 ng algorithms including unsupervised methods (Clustering\, Association Rul
 es) and supervised ones (Decision Trees\, Naive Bayes\, Random Forests and
  Deep Neural Network). Basic Machine Learning concepts such as training se
 t\, test set\, validation set\, overfitting\, bagging\, boosting will be i
 ntroduced as well as performance evaluation for supervised and unsupervise
 d methods.\n\nThe second part will consist of practical exercises such as 
 reading data\, using packages and building machine learning applications. 
 Different options for parallel programming will be shown using specific R 
 packages (parallel\, h2o\,…). For Deep Learning applications the Keras p
 ackage will be presented. The examples will cover the analysis of large da
 tasets and images datasets. Participants will use R on Cineca HPC faciliti
 es for practical assignments.\n\nSkills:\nAt the end of the course\, the s
 tudent will be expected to have acquired:\n    • the ability to perfor
 m basic operations on matrices and dataframes \n    • the ability to 
 manage packages\n    • the ability to navigate in the RStudio interfac
 e\n    • a general knowledge of Machine and Deep Learning methods\n  
   • a general knowledge of the most popular packages for Machine and De
 ep Learning\n    • a basic knowledge of different parallel programming
  techniques\n    • the ability to build machine learning applications 
 with large datasets and images datasets\n\nTarget audience:\nStudents and 
 researchers with different backgrounds\, looking for technologies and meth
 ods to analyze a large amount of data.\n\nPre-requisites:\nParticipants mu
 st have a basic statistics knowledge. Participants must also be familiar w
 ith basic Linux and R language.\n\n\nThe number of participants is limited
  to 25 students.\nApplicants will be selected according to their experienc
 e\, qualifications and scientific interest BASED ON WHAT WRITTEN IN THE R
 EGISTRATION FORM.\n\nPlease use the "Reason for Participation" field for w
 riting your background and for motivating your subscription to an R course
 .\n\nAPPLICATION DEADLINE:  JAN 2nd 2022\n \n\nSTUDENTS ADMITTED AND NO
 T ADMITTED WILL BE CONTACTED VIA EMAIL ON JAN 10th 2022.\n\n\nIF YOU SUBM
 ITTED AND DIDN'T RECEIVE THE EMAIL AT THAT DATE\, PLEASE WRITE AT corsi.h
 pc@cineca.it.  \nhttps://events.prace-ri.eu/event/1305/
SUMMARY:[ONLINE]Data science with R @ Cineca
URL;VALUE=URI:https://events.prace-ri.eu/event/1305/
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