# fizaan-ali/ml-specialization-course-1-practice architecture

> Architecture diagram of the GitHub repository fizaan-ali/ml-specialization-course-1-practice, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-11-12). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/fizaan-ali/ml-specialization-course-1-practice
- Repository: https://github.com/fizaan-ali/ml-specialization-course-1-practice

## Overview

This is a personal supervised-machine-learning study archive, not a deployed prediction service. A learner opens topic-organized notebooks to work through regression, classification, regularization, and NumPy/plotting exercises; some exercises use the included CSV practice data and reusable Python helpers. The README documents the topic coverage and dataset-loading convention. Notebook contents were not sampled, so links from particular notebooks to particular helpers or datasets are not asserted.

Main entry points: [`data`](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/data) (Practice datasets), [`src/regression_module.py`](https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/regression_module.py) (Regression helpers), [`src/logistic_module.py`](https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/logistic_module.py) (Logistic helpers), [`notebooks/linear_regression`](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/linear_regression) (Linear regression)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_learning["Notebook lessons"]
  node_linear["Linear regression"]
  node_logistic["Logistic regression"]
  node_regularization["Regularization"]
  node_numpy_plotting["NumPy and plotting"]
end

subgraph group_helpers["Reusable helpers"]
  node_regression_helpers["Regression helpers"]
  node_multiple_helpers["Multiple regression helpers"]
  node_logistic_helpers["Logistic helpers<br/>[logistic_module.py]"]
end

subgraph group_datasets["Practice data"]
  node_csv_data["Practice datasets"]
end

node_learner(("Learner"))

node_learner -->|"studies"| node_linear
node_learner -->|"studies"| node_logistic
node_learner -->|"studies"| node_regularization
node_learner -->|"studies"| node_numpy_plotting
node_regression_helpers -->|"loads house data"| node_csv_data
node_logistic_helpers -->|"loads CSV data"| node_csv_data

click node_linear "https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/linear_regression"
click node_logistic "https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/logistic_regression"
click node_regularization "https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/regularization"
click node_numpy_plotting "https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/numpy_and_plotting"
click node_regression_helpers "https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/regression_module.py"
click node_multiple_helpers "https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/multiple_regression_helpers.py"
click node_logistic_helpers "https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/logistic_module.py"
click node_csv_data "https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/data"

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_linear,node_logistic,node_regularization,node_numpy_plotting toneBlue
class node_regression_helpers,node_multiple_helpers,node_logistic_helpers toneAmber
class node_csv_data toneMint
class node_learner toneIndigo
```

## Components

### Notebook lessons

- [Linear regression](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/linear_regression): `notebooks/linear_regression`
- [Logistic regression](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/logistic_regression): `notebooks/logistic_regression`
- [Regularization](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/regularization): `notebooks/regularization`
- [NumPy and plotting](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/notebooks/numpy_and_plotting): `notebooks/numpy_and_plotting`

### Reusable helpers

- [Regression helpers](https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/regression_module.py): `src/regression_module.py`
- [Multiple regression helpers](https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/multiple_regression_helpers.py): `src/multiple_regression_helpers.py`
- [Logistic helpers](https://github.com/fizaan-ali/ml-specialization-course-1-practice/blob/main/src/logistic_module.py): `src/logistic_module.py`

### Practice data

- [Practice datasets](https://github.com/fizaan-ali/ml-specialization-course-1-practice/tree/main/data): `data`

### Other components

- **Learner**

## Connections

- Learner → Linear regression: studies (evidence: `README.md`)
- Learner → Logistic regression: studies (evidence: `README.md`)
- Learner → Regularization: studies (evidence: `README.md`)
- Learner → NumPy and plotting: studies (evidence: `README.md`)
- Regression helpers → Practice datasets: loads house data (evidence: `src/regression_module.py`)
- Logistic helpers → Practice datasets: loads CSV data (evidence: `src/logistic_module.py`)