Detail předmětu
Dátova věda s iphytonem a jupyterem
CEITEC VUT-DS119Ak. rok: 2020/2021
Within this course parts of statistics, data analysis and machine learning methods will be covered. The main focus will be on implementation of the methods, visualization and interpretation of the derived results.
Jazyk výuky
angličtina
Garant předmětu
Zajišťuje ústav
Prerekvizity
Basic programming knowledge
Způsob a kritéria hodnocení
60% completing a small data science project, 40% Examination
Osnovy výuky
python basics, the python libraries numpy, pandas and tensorflow
- basics of ipython and jupyter notebooks
- collect data from different sources, experiment, simulation or www
- adjust the collected data for the needs of the planned analysis
- performing the required statistical analysis on the data
- deriving conclusion and or making predictions
- basics of ipython and jupyter notebooks
- collect data from different sources, experiment, simulation or www
- adjust the collected data for the needs of the planned analysis
- performing the required statistical analysis on the data
- deriving conclusion and or making predictions
Základní literatura
Deep Learning, Ian Goodfellow and Yoshua Bengio and Aaron Courville, MIT Press, 2016 (EN)
pandas documentation: https://pandas.pydata.org/pandas-docs/stable/ (EN)
tensorflow documentation: https://www.tensorflow.org/api_doc (EN)
pandas documentation: https://pandas.pydata.org/pandas-docs/stable/ (EN)
tensorflow documentation: https://www.tensorflow.org/api_doc (EN)