Metadata-Version: 2.4
Name: practical08
Version: 0.6.1
Summary: Dataset-first AIML practical code and Units I-IV theory revision helper
Author: Practical08 contributors
License: MIT License
        
        Copyright (c) 2026 Practical08 contributors
        
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Requires-Python: >=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pandas>=1.5
Requires-Dist: numpy>=1.23
Requires-Dist: scikit-learn>=1.2
Requires-Dist: matplotlib>=3.6
Dynamic: license-file

# Practical08 v0.6.1

Practical08 is a dataset-first helper for 26 AIML practicals plus concise theory revision for Units I–VI.

## Usage

```python
from practical08 import ask

ask("Titanic")                 # preprocessing practical
ask("Iris Dataset")            # compare K values in KNN
ask("Heart Disease Dataset")   # Bagging vs Boosting
ask("Bank Marketing Dataset")  # term-deposit classification
ask("theory")                  # all theory concepts in Units I–VI
ask("Unit 2 theory")            # regression theory only
```

The generated code asks for the local CSV path and relevant column names where required. Dataset names and column names vary across public sources, so enter the names printed by the program. Some examples use built-in scikit-learn data; 20 Newsgroups may need internet on first use. Apriori examples require `mlxtend` (`python -m pip install mlxtend`).

## Install

```bash
python -m pip install --upgrade practical08==0.6.0
```

In Jupyter, use `%pip install --upgrade practical08==0.6.0`.

## Important

This version replaces the previous program catalog with the 26 practicals specified for this release. It does not bundle third-party datasets. The printed code is a template and may need column-name selection to match the exact CSV variant you downloaded.


## Theory coverage

Theory mode now covers Units I–VI, including Ensemble Learning (Unit V) and Reinforcement Learning (Unit VI). Use `ask('theory')` for all units, or `ask('Unit 5 theory')` and `ask('Unit 6 theory')` for individual units.
