Metadata-Version: 2.4
Name: practical01
Version: 0.1.1
Summary: Machine Learning practicals and viva questions
Requires-Python: >=3.10
Description-Content-Type: text/markdown
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: scikit-learn
Requires-Dist: matplotlib
Dynamic: description
Dynamic: description-content-type
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# practical01 — Machine Learning Practicals

This package is based on the 26 titles in `Practical List-ML.pdf`. It provides a searchable catalogue, runnable teaching/demo code, and five viva questions for each practical.

## Important dataset note
The PDF contains practical titles only, not the actual CSV files, exact column names, required code, or expected outputs. Therefore several programs use reproducible demonstration data so that they can run without private dataset files. Replace demo data with your instructor's CSV when required. Output values are produced at runtime and can differ by dataset and package version.

## Install locally
```bash
python -m pip install .
```

## Use in Jupyter Notebook
```python
from practical01 import ask, list_practicals
ask(4)
ask("KNN")
list_practicals()
```

## Share with friends
Upload the project folder to GitHub. Friends can install it using:
```python
%pip install git+https://github.com/YOUR-USERNAME/practical01.git
```
Replace the URL with the actual repository URL. To publish on PyPI later, choose a package name that is available and follow PyPI publishing steps.

## Dependencies
Core dependencies are installed with the package. Practical 12 and 24 need `mlxtend`:
```python
%pip install mlxtend
```
Practical 16 downloads the 20 Newsgroups dataset the first time it runs, so internet access is required for that first run.
