Initial commit
commit
abfc8de8e8
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# ---> JupyterNotebooks
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# gitignore template for Jupyter Notebooks
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# website: http://jupyter.org/
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.ipynb_checkpoints
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*/.ipynb_checkpoints/*
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# IPython
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profile_default/
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ipython_config.py
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# Remove previous ipynb_checkpoints
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# git rm -r .ipynb_checkpoints/
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# ---> Python
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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||||
*.spec
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||||
|
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# Installer logs
|
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pip-log.txt
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pip-delete-this-directory.txt
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|
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# Unit test / coverage reports
|
||||
htmlcov/
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.tox/
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.nox/
|
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.coverage
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.coverage.*
|
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.cache
|
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nosetests.xml
|
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coverage.xml
|
||||
*.cover
|
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*.py,cover
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.hypothesis/
|
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.pytest_cache/
|
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cover/
|
||||
|
||||
# Translations
|
||||
*.mo
|
||||
*.pot
|
||||
|
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# Django stuff:
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*.log
|
||||
local_settings.py
|
||||
db.sqlite3
|
||||
db.sqlite3-journal
|
||||
|
||||
# Flask stuff:
|
||||
instance/
|
||||
.webassets-cache
|
||||
|
||||
# Scrapy stuff:
|
||||
.scrapy
|
||||
|
||||
# Sphinx documentation
|
||||
docs/_build/
|
||||
|
||||
# PyBuilder
|
||||
.pybuilder/
|
||||
target/
|
||||
|
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# Jupyter Notebook
|
||||
.ipynb_checkpoints
|
||||
|
||||
# IPython
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||||
profile_default/
|
||||
ipython_config.py
|
||||
|
||||
# pyenv
|
||||
# For a library or package, you might want to ignore these files since the code is
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||||
# intended to run in multiple environments; otherwise, check them in:
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# .python-version
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||||
|
||||
# pipenv
|
||||
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
|
||||
# However, in case of collaboration, if having platform-specific dependencies or dependencies
|
||||
# having no cross-platform support, pipenv may install dependencies that don't work, or not
|
||||
# install all needed dependencies.
|
||||
#Pipfile.lock
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||||
|
||||
# poetry
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||||
# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
|
||||
# This is especially recommended for binary packages to ensure reproducibility, and is more
|
||||
# commonly ignored for libraries.
|
||||
# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
|
||||
#poetry.lock
|
||||
|
||||
# pdm
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||||
# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
||||
#pdm.lock
|
||||
# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
|
||||
# in version control.
|
||||
# https://pdm.fming.dev/#use-with-ide
|
||||
.pdm.toml
|
||||
|
||||
# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
|
||||
__pypackages__/
|
||||
|
||||
# Celery stuff
|
||||
celerybeat-schedule
|
||||
celerybeat.pid
|
||||
|
||||
# SageMath parsed files
|
||||
*.sage.py
|
||||
|
||||
# Environments
|
||||
.env
|
||||
.venv
|
||||
env/
|
||||
venv/
|
||||
ENV/
|
||||
env.bak/
|
||||
venv.bak/
|
||||
|
||||
# Spyder project settings
|
||||
.spyderproject
|
||||
.spyproject
|
||||
|
||||
# Rope project settings
|
||||
.ropeproject
|
||||
|
||||
# mkdocs documentation
|
||||
/site
|
||||
|
||||
# mypy
|
||||
.mypy_cache/
|
||||
.dmypy.json
|
||||
dmypy.json
|
||||
|
||||
# Pyre type checker
|
||||
.pyre/
|
||||
|
||||
# pytype static type analyzer
|
||||
.pytype/
|
||||
|
||||
# Cython debug symbols
|
||||
cython_debug/
|
||||
|
||||
# PyCharm
|
||||
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
|
||||
# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
|
||||
# and can be added to the global gitignore or merged into this file. For a more nuclear
|
||||
# option (not recommended) you can uncomment the following to ignore the entire idea folder.
|
||||
#.idea/
|
||||
|
||||
|
|
@ -0,0 +1,27 @@
|
|||
# CDS1011_A2
|
||||
|
||||
Für die folgenden Aufträge können Sie je nach Vorkenntnisse beliebige Tools (Python, Excel, R, Matlab, Tableau) nützen. Eigene Programmierungen sind notwendig zur Lösung der Aufgabe. Lösen Sie die Aufgabe in kleinen Gruppen (2-3 Personen).
|
||||
|
||||
Auftrag (angelehnt an die Checkliste im Anhang B aus der Literatur)
|
||||
Fragestellung definieren
|
||||
Beschaffen Sie sich Daten.
|
||||
Erkunden Sie die Daten, um daraus Erkenntnisse zu gewinnen.
|
||||
Bereiten Sie die Daten so auf, dass Machine-Learning-Algorithmen die Muster darin leichter erkennen können.
|
||||
Probieren Sie 2-3 Modelle aus und treffen Sie eine engere Auswahl.
|
||||
Optimieren Sie Ihre Modelle und kombinieren Sie diese zu einer guten Lösung.
|
||||
Dokumentieren Sie die Erkenntnisse
|
||||
Deployment und Überwachung des Systems (optional)
|
||||
Fragestellung und Datensatz aus dem ersten Leistungsnachweis kann übernommen oder weiterentwickelt werden, oder eine neue Fragestellung mit einem neuen Datensatz (eigenen oder fremden) wird bearbeitet
|
||||
Dokumentieren Sie die Erkenntnisse in Form eines wissenschaftlichen Berichts (LaTeX Vorlage für Semesterarbeit)
|
||||
Möglicher Inhalt
|
||||
Einleitung
|
||||
Stand der Forschung
|
||||
Forschungsfrage(n) und Methodik
|
||||
Resultate
|
||||
Diskussion
|
||||
Zusammenfassung
|
||||
Ausblick
|
||||
Umfang
|
||||
2-3 Seiten
|
||||
Zitate
|
||||
APA
|
||||
Loading…
Reference in New Issue