nlp-playground

Natural Language Processing playground to play around and learn NLP related skills.

---
config:
  look: handDrawn
  theme: neutral
---
flowchart LR
    subgraph AI["Artificial Intelligence"]
        direction TB
        subgraph ML["Machine Learning"]
            direction TB
            DL("Deep Learning")
        end
        Robotics("Robotics")
        KRR("Knowledge\nRepresentation\n& Reasoning")
        CV("Computer\nVision")
        NLP("Natural\nLanguage\nProcessing")
        NLP -.- ML
        KRR -.- ML
        ML -.- CV
        ML -.- Robotics
    end
    subgraph DS["Data Science"]
        direction LR
        DV("Data\nVisualization")
        SI("Statistical\nInference")
        Math("Mathematics")
        Stats("Statistics")
        DA("Data\nAnalysis")
        DE("Data\nEngineering")
        DM("Data\nMining")
        More("...")
        DV ~~~ SI
        Math ~~~ Stats
        DA ~~~ DE
        DM ~~~ More
    end
    AI -.- DS
    classDef highlight fill:#bbb,stroke-width:3px,color:#000
    class NLP highlight

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References

• https://github.com/sfmunoz/introtonlp-365 (initially cloned from https://github.com/l-newbould/introtonlp-365)
• ENTIRE Natural Language Processing CRASH COURSE in 45 MINS!

Library Dependencies

---
config:
  look: handDrawn
  theme: neutral
---
graph TD
    jupyterlab(JupyterLab)
    notebook(Notebook)
    ipykernel(IPython Kernel)
    numpy(NumPy)
    matplotlib(Matplotlib)
    pandas(Pandas)
    seaborn(Seaborn)
    nltk(NLTK)
    spacy(spaCy)

    jupyterlab --> ipykernel
    notebook --> ipykernel
    matplotlib --> numpy
    pandas --> numpy
    seaborn --> numpy
    seaborn --> pandas
    seaborn --> matplotlib
    nltk -.-> matplotlib
    nltk -.-> numpy
    spacy --> numpy
    spacy -.-> matplotlib

    classDef highlight fill:#bbb,stroke-width:3px,color:#000
    %%class jupyterlab,notebook,ipykernel highlight

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Jupyter Lab execution

To run Jupyter Lab use the run.sh script in the root of the project (virtualenv is automatically created by uv):

$ ./run.sh

Git commit workflow

It's enough to user jupyter nbconvert --clear-output by hand to keep it simple (for now):

$ git add some_file.ipynb

$ uv run jupyter nbconvert some_file.ipynb --clear-output

$ git diff --staged
  (... check the full diff ...)

$ git diff
  (... check "execution=null" and "outputs=[]" ...)

$ git add some_file.ipynb

$ git diff
  (... check final diff ...)

$ git commit ...

---

⚠️ (legacy) Anaconda setup

Even though there are thinner alternatives I'm using Anaconda to have as much software available as possible:

• Go to https://www.anaconda.com/ → (Free Downdload) → https://www.anaconda.com/download
• Download Anaconda Distribution → https://repo.anaconda.com/archive/Anaconda3-2025.12-2-Linux-x86_64.sh

It's quite large:

$ ls -l Anaconda3-2025.12-2-Linux-x86_64.sh
-rw-rw-r-- 1 sfm sfm 1277826351 May  9 16:26 Anaconda3-2025.12-2-Linux-x86_64.sh

I'm using an already created /anaconda3 folder. Even though it's empty option -u (update an existing installation) must be provided to avoid messages like:

$ bash Anaconda3-2025.12-2-Linux-x86_64.sh -p /anaconda3
(...)
ERROR: File or directory already exists: '/anaconda3'.
If you want to update an existing installation, use the -u option.

So -u option is used:

$ bash Anaconda3-2025.12-2-Linux-x86_64.sh -p /anaconda3 -u
(...)
Preparing transaction: done
Executing transaction: done
installation finished.
WARNING:
    You currently have a PYTHONPATH environment variable set. This may cause
    unexpected behavior when running the Python interpreter in Anaconda3.
    For best results, please verify that your PYTHONPATH only points to
    directories of packages that are compatible with the Python interpreter
    in Anaconda3: /anaconda3
Do you wish to update your shell profile to automatically initialize conda?
This will activate conda on startup and change the command prompt when activated.
If you'd prefer that conda's base environment not be activated on startup,
   run the following command when conda is activated:

conda config --set auto_activate_base false

Note: You can undo this later by running `conda init --reverse $SHELL`

Proceed with initialization? [yes|no]
[no] >>> no

You have chosen to not have conda modify your shell scripts at all.
To activate conda's base environment in your current shell session:

eval "$(/anaconda3/bin/conda shell.YOUR_SHELL_NAME hook)"

To install conda's shell functions for easier access, first activate, then:

conda init

Thank you for installing Anaconda3!

⚠️ (legacy) Conda activate

$ eval "$(/anaconda3/bin/conda shell.zsh hook)"

⚠️ (legacy) Conda deactivate

$ conda deactivate

⚠️ (legacy) Jupyter Lab execution

To run Jupyter Lab using Anaconda3 set LEGACY=1 before using run.sh (some notebooks still need this to find the required libraries):

$ LEGACY=1 ./run.sh