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restruture old ch02 into appendix A
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appendix-A/02_installing-python-libraries/README.md
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appendix-A/02_installing-python-libraries/README.md
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# Libraries Used In This Workshop
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We will be using the following libraries in this workshop, and I highly recommend installing them before attending the event:
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- numpy >= 1.24.3 (The fundamental package for scientific computing with Python)
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- scipy >= 1.10.1 (Additional functions for NumPy)
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- pandas >= 2.0.2 (A data frame library)
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- matplotlib >= 3.7.1 (A plotting library)
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- jupyterlab >= 4.0 (An application for running Jupyter notebooks)
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- ipywidgets >= 8.0.6 (Fixes progress bar issues in Jupyter Lab)
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- scikit-learn >= 1.2.2 (A general machine learning library)
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- watermark >= 2.4.2 (An IPython/Jupyter extension for printing package information)
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- torch >= 2.0.1 (The PyTorch deep learning library)
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- torchvision >= 0.15.2 (PyTorch utilities for computer vision)
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- torchmetrics >= 0.11.4 (Metrics for PyTorch)
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- transformers >= 4.30.2 (Language transformers and LLMs for PyTorch)
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- lightning >= 2.0.3 (A library for advanced PyTorch features: multi-GPU, mixed-precision etc.)
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To install these requirements most conveniently, you can use the `requirements.txt` file:
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```
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pip install -r requirements.txt
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```
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Then, after completing the installation, please check if all the packages are installed and are up to date using
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```
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python_environment_check.py
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```
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It's also recommended to check the versions in JupyterLab by running the `jupyter_environment_check.ipynb` in this directory. Ideally, it should look like as follows:
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If you see the following issues, it's likely that your JupyterLab instance is connected to wrong conda environment:
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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:
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