The purpose of this workshop is to provide a crash-course introduction to the state-of-the-art Machine Learning techniques currently used in solving software engineering problems involving Natural Language.
While touching on theoretical principles, the course will be geared specifically towards practical applications commonly encountered in Natural Language Processing. The main techniques discussed will be: Language Modelling, Distributional Semantics, Text Classification, and Deep Learning as applied to Natural Language Processing.
The course will specifically emphasize the newer, Deep Learning techniques that are becoming popular at companies like Google, Facebook, and Twitter, and will provide an introduction a few of the Open Source libraries that these companies sponsor.
Applications discussed include Spam Filtering, Topic Modelling, Text Regeneration, and Text-based Recommender Systems.
At the end of this workshop, you will be familiar with:
The workshop would take place over the course of two weeks, and involve 10 hours of demonstrative lectures together with 5 hours of hands-on practicals. It is aimed at a target audience of 12-15 attendants.
During the first week, there will be a maximum of 2 hours of demonstrative lectures every day, followed by one hour of hands-on practicals in which the principles taught will be put to use via self-contained applications that involve popular Open Source Machine Learning toolkits and solutions.
An outline of the curriculum covered in the demonstrative lectures and hands-on sessions of the first week is given below:
Nota Bene: The curriculum is subject to minor modifications without prior notice, depending on external planning factors.
During the second week, there will be four consecutive Hackathon sessions, aiming to come up with prototypes to an engineering problem. Only four places exist for the project, and the participants from the first week who wish to stay on and do the project will be selected based on availability and project affinity, and announced on June 20th, 2015.
The title of the project will be:
The course will be taught entirely in English, and is aimed for Computer Science and Computer Engineering students in their 2nd, 3rd, or 4th year of studies with a good background in software engineering, as well as to fresh members of the industry who wish to further their knowledge of Machine Learning as it is applied to problems in Natural Language Processing. The following are the minimum prerequisites for attending:
Registration for the workshop was possible using the online Registration Form. Registration closed on June 7th, at 23:59 Bucharest Time.
Registrants were announced of the outcome of their application by email on June 9th, 2015. The selected course participants were:
|Participant Name||Participant Affiliation|
|First Last||Faculty||University||Position||Week 2 Hackathon|
|Andrei Stefan Tuicu||ACS||Politehnica University of Bucharest||Undergraduate, Year 3||✓|
|Andrei-Vlad Fulgeanu||ACS||Politehnica University of Bucharest||Undergraduate, Year 4||✓|
|Teodor Szente||N/A (high scool)||Cantemir Voda National College||Student|
|Gabriel Rotaru||ACS||Politehnica University of Bucharest||Undergraduate, Year 2|
|Bogdan Merlusca||FILS||Politehnica University of Bucharest||Graduated, Class of 2007|
|Vlad-Ovidiu Lupu||FMI||University of Bucharest||Undergraduate, Year 2|
|Eduard Lache||ACS||Politehnica University of Bucharest||Undergraduate, Year 2||✓|
|Daniel Dogaru||ACS||Politehnica University of Bucharest||Undergraduate, Year 4||✓|
|George-Cristian Muraru||ACS||Politehnica University of Bucharest||Undergraduate, Year 2||✓|
|Ioana-Alina Bănică||ETTI||Politehnica University of Bucharest||Undergraduate, Year 4|
|Eduard George Ionescu||FMI||University of Bucharest||Undergraduate, Year 1|
|Vladu Ana Maria||ETTI||Politehnica University of Bucharest||Undergraduate, Year 4|
|Matei Popovici||ACS||Politehnica University of Bucharest||Lecturer|
ACS - Faculty of Automatic Control and Computer Science
FMI - Faculty of Mathematics and Informatics
FILS - Faculty of Engineering in Foreign Languages
ETI - Faculty of Electronics, Telecommunication and Information Technology