Please enable JavaScript.
Coggle requires JavaScript to display documents.
Data analytic Web apps (data and anomaly exploration software) for TE-MPE…
Data analytic Web apps (data and anomaly exploration software) for TE-MPE (CERN)
RESEARCH [WP2]
Machine Learning techniques for anomaly detection and data exploration
Machine learning and data visualisation
[RapidMiner] (
https://rapidminer.com/
)
[Sci-learn kit] (
http://scikit-learn.org/stable/
)
[Bokeh] (
http://bokeh.pydata.org/en/latest/
)
Deep learning (DL)
[Keras] (
https://keras.io/
)
Hardware implementation of DL techniques for optimisation
DEFINING USER REQUIERMENTS [WP1]
Expertise in the field - data technology lectures, materials, courses
Data exploration (clustering)
Detecting anomalies (DL techniques)
RapidMiner prototyping
Use cases of analysis, various fields (potentials and use of the technology)
Defining use cases
Study of documentation
Brainstorming
...:pen:
Interdisciplinary work
Examples of use in TE-MPE
Electrical quality assurance
...:pen:
Quench detection
Characteristics
Integration with CERN data analytics paradigm
Potential in different scenarios of TE-MPE
:pen:...
STUDENT PRACTICES [WP4]
Data visualization
Python programming
:pen:...
ORGANZATIONS AND COMPANIES
Slovenia
[Alma Mater Europaea, European Centre Maribor, Slovenia] (
http://en.almamater.si/?checkCo=true
)
Poland
[Faculty of Computer Science, Electronics and Telecommunications, AGH University of Science and Technology, Kraków] (
http://www.agh.edu.pl/en/wydzialy/wydzial-informatyki-elektroniki-itelekomunikacji/
)
:pen:...
APPLICATONS [WP3]
Developement of software apps for TE-MPE-EE
Prototyping
Python framework
Iterative design
USING EXPERIENCES FROM DATA ANALYITICS SOFTWARE DEVELOPMENT AT TE-MPE-EE