latinet:unicaes:start
UNICAES Python Workshop - 2022-09-01
Workshop by Clein Sarmiento and Rolf Becker from HSRW on 2022-09-01
Fig.: Great audience! |
Import Antigravity
Fig.: Import antigravity. Source: https://xkcd.com/353/ |
Preparation
- Install the Anaconda Python Data Science Suite
- Download unicaes_ws_v002.zip containing the workshop Python code
Code Snippets to Handle the Conda Environment
This code is to be executed in a terminal. I extended the list of software packages to be installed to run all provided workshop examples. Mac and Linux users just open a standard terminal. On Windows open the Anaconda Powershell prompt.
Execute the following code:
# create conda environment including installation of all necessary packages conda create -c conda-forge -n unicaes jupyterlab ipywidgets numpy pandas scipy scikit-learn matplotlib plotly seaborn # activate conda environment conda activate unicaes # start Jupyter-Lab (<Ctrl>-C in the terminal to exit jupyter-lab) jupyter-lab # leave conda envoronment and change to the base (default) environment conda deactivate # remove environment (in case you want to delete it) # conda env remove -n unicaes
Code Snippets to Handle the Conda Environment
This code is to be executed in a terminal. I extended the list of software packages to be installed to run all provided workshop examples. Mac and Linux users just open a standard terminal. On Windows open the Anaconda Powershell prompt.
Execute the following code:
# create conda environment including installation of all necessary packages conda create -c conda-forge -n unicaes jupyterlab ipywidgets numpy pandas scipy scikit-learn matplotlib plotly seaborn # activate conda environment conda activate unicaes # start Jupyter-Lab (<Ctrl>-C in the terminal to exit jupyter-lab) jupyter-lab # leave conda envoronment and change to the base (default) environment conda deactivate # remove environment (in case you want to delete it) # conda env remove -n unicaes
Video Recordings (unfortunately with very bad sound quality)
- Part 1: https://youtu.be/3x-HB5OIHwg
- Part 2: https://youtu.be/eLAwMHvp8EE
Additional Information
- Python tutorial from CS231n: Deep Learning for Computer Vision Course at Stanford
- CS231n Github Repo
latinet/unicaes/start.txt · Last modified: 2023/01/05 14:38 by 127.0.0.1