# shreelakshmigbhat/ml_practice_notebooks architecture

> Architecture diagram of the GitHub repository shreelakshmigbhat/ml_practice_notebooks, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-28). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/shreelakshmigbhat/ml_practice_notebooks
- Repository: https://github.com/shreelakshmigbhat/ml_practice_notebooks

## Overview

This repository is an educational collection of machine-learning notebooks, organized around supervised and unsupervised learning rather than a packaged application. The main workflow is a learner studying a notebook that demonstrates an algorithm with datasets and visualizations. The README documents additional algorithms beyond the sampled source; their exact notebook-level wiring is not established. The sampled SVM GUI separately trains a classifier from local animal images and predicts labels for selected images.

Main entry points: [`Supervised Learning/classifications/svm_gui.py`](https://github.com/shreelakshmigbhat/ml_practice_notebooks/blob/main/Supervised%20Learning/classifications/svm_gui.py) (Cat-Dog SVM GUI), [`Supervised Learning/classifications`](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/classifications) (Classification Notebooks), [`Supervised Learning/regressions`](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/regressions) (Regression Notebooks), [`Unsupervised/Clustering`](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Unsupervised/Clustering) (Clustering Notebooks)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_supervised["Supervised Learning"]
  node_classify["Classification Notebooks"]
  node_regress["Regression Notebooks"]
  node_classdata["Classification Data"]
  node_regdata["Regression Data"]
end

subgraph group_unsupervised["Unsupervised Learning"]
  node_cluster["Clustering Notebooks"]
  node_clusterdata["Clustering Data"]
end

subgraph group_support["Interactive Example"]
  node_gui["Cat-Dog SVM GUI<br/>[svm_gui.py]"]
  node_svmmodel["Trained SVM<br/>[svm_gui.py]"]
end

node_learner(("Learner"))
node_animalimages[("Local Animal Images")]
node_selectedimage["Selected Image"]
node_prediction["Cat-Dog Prediction"]
node_mltools["Python ML Libraries"]

node_learner -->|"studies"| node_classify
node_learner -->|"studies"| node_regress
node_learner -->|"studies"| node_cluster
node_classify -->|"uses examples"| node_classdata
node_regress -->|"uses examples"| node_regdata
node_cluster -->|"uses examples"| node_clusterdata
node_animalimages -->|"loads for training"| node_gui
node_gui -->|"trains"| node_svmmodel
node_mltools -->|"provides SVM"| node_gui
node_gui -->|"opens image"| node_selectedimage
node_gui -->|"predicts with"| node_svmmodel
node_svmmodel -->|"returns label"| node_prediction

click node_classify "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/classifications"
click node_regress "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/regressions"
click node_classdata "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/classifications"
click node_regdata "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/regressions"
click node_cluster "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Unsupervised/Clustering"
click node_clusterdata "https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Unsupervised/Clustering"
click node_gui "https://github.com/shreelakshmigbhat/ml_practice_notebooks/blob/main/Supervised%20Learning/classifications/svm_gui.py"
click node_svmmodel "https://github.com/shreelakshmigbhat/ml_practice_notebooks/blob/main/Supervised%20Learning/classifications/svm_gui.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_classify,node_regress,node_classdata,node_regdata toneBlue
class node_cluster,node_clusterdata,node_animalimages toneAmber
class node_gui,node_svmmodel toneMint
class node_learner,node_selectedimage,node_prediction,node_mltools toneIndigo
```

## Components

### Supervised Learning

- [Classification Notebooks](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/classifications): `Supervised Learning/classifications`
- [Regression Notebooks](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/regressions): `Supervised Learning/regressions`
- [Classification Data](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/classifications): `Supervised Learning/classifications`
- [Regression Data](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Supervised%20Learning/regressions): `Supervised Learning/regressions`

### Unsupervised Learning

- [Clustering Notebooks](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Unsupervised/Clustering): `Unsupervised/Clustering`
- [Clustering Data](https://github.com/shreelakshmigbhat/ml_practice_notebooks/tree/main/Unsupervised/Clustering): `Unsupervised/Clustering`

### Interactive Example

- [Cat-Dog SVM GUI](https://github.com/shreelakshmigbhat/ml_practice_notebooks/blob/main/Supervised%20Learning/classifications/svm_gui.py): `Supervised Learning/classifications/svm_gui.py`
- [Trained SVM](https://github.com/shreelakshmigbhat/ml_practice_notebooks/blob/main/Supervised%20Learning/classifications/svm_gui.py): `Supervised Learning/classifications/svm_gui.py`

### Other components

- **Learner**
- **Local Animal Images**
- **Selected Image**
- **Cat-Dog Prediction**
- **Python ML Libraries**

## Connections

- Learner → Classification Notebooks: studies
- Learner → Regression Notebooks: studies
- Learner → Clustering Notebooks: studies
- Classification Notebooks → Classification Data: uses examples
- Regression Notebooks → Regression Data: uses examples
- Clustering Notebooks → Clustering Data: uses examples
- Local Animal Images → Cat-Dog SVM GUI: loads for training
- Cat-Dog SVM GUI → Trained SVM: trains
- Python ML Libraries → Cat-Dog SVM GUI: provides SVM
- Cat-Dog SVM GUI → Selected Image: opens image
- Cat-Dog SVM GUI → Trained SVM: predicts with
- Trained SVM → Cat-Dog Prediction: returns label