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00-2_python-libraries-for-workshop

Libraries Used In This Workshop

We will be using the following libraries in this workshop, and I highly recommend installing them before attending the event:

  • numpy >= 1.24.3 (The fundamental package for scientific computing with Python)
  • scipy >= 1.10.1 (Additional functions for NumPy)
  • pandas >= 2.0.2 (A data frame library)
  • matplotlib >= 3.7.1 (A plotting library)
  • jupyterlab >= 4.0 (An application for running Jupyter notebooks)
  • ipywidgets >= 8.0.6 (Fixes progress bar issues in Jupyter Lab)
  • scikit-learn >= 1.2.2 (A general machine learning library)
  • mlxtend >= 0.22 (Additional machine learning utilities)
  • watermark >= 2.4.2 (An IPython/Jupyter extension for printing package information)
  • torch >= 2.0.1 (The PyTorch deep learning library)
  • torchvision >= 0.15.2 (PyTorch utilities for computer vision)
  • torchmetrics >= 0.11.4 (Metrics for PyTorch)
  • transformers >= 4.30.2 (Language transformers and LLMs for PyTorch)
  • lightning >= 2.0.3 (A library for advanced PyTorch features: multi-GPU, mixed-precision etc.)

To install these requirements most conveniently, you can use the requirements.txt file. Assuming you are in the top level of this GitHub repository, you can execute the following code:

cd 00-2_python-libraries-for-workshop

pip install -r requirements.txt

install-requirements

Then, after completing the installation, please check if all the packages are installed and are up to date using the following command:

python python_environment_check.py

check_1

It's also recommended to check the versions in JupyterLab by running the jupyter_environment_check.ipynb in this directory. To open JupyterLab, execute the following command in your terminal:

jupyter lab

Then, open the jupyter_environment_check.ipynb file and execute all cells.

Ideally, the resulting outputs should look like as follows:

check_1

If you see the following issues, it's likely that your JupyterLab instance is connected to wrong conda environment:

jupyter-issues

In this case, you may want to use watermark to check if you opened the JupyterLab instance in the right conda environment using the --conda flag:

watermark

If you need additional help, please don't hesitate to reach out via the Discussion board.