Metadata-Version: 2.4
Name: DLdemo
Version: 1.0.0
Summary: Deep Learning practical demo code grouped into five assignment modules
Requires-Python: >=3.9
Description-Content-Type: text/markdown

# DLdemo

`DLdemo` is a five-model demo library based directly on the five modules
of the supplied Deep Learning practical assignment.

## Exact usage

```python
import DLdemo.demo as demo

print(demo.modelS)   # Module 1: Single-Neuron
print(demo.modelP)   # Module 2: Perceptron
print(demo.modelK)   # Module 3: Keras MLP
print(demo.modelF)   # Module 4: Forward & Backpropagation
print(demo.modelL)   # Module 5: Loss Functions
```

Each variable contains the complete source code for that module as a string.

## Five models

- `modelS` → Module 1, Q1-Q4: Single-Neuron Predictive Models
- `modelP` → Module 2, Q5-Q8: Perceptron Learning Formula & Decision Rules
- `modelK` → Module 3, Q9-Q12: Multi-Layer Perceptron (MLP) Using Keras
- `modelF` → Module 4, Q13-Q16: Forward and Backpropagation Implementation
- `modelL` → Module 5, Q17-Q20: Loss Functions Implementation & Comparison

The source files contain step-wise comments explaining:
1. Dataset loading
2. Data preprocessing
3. Train/test splitting
4. Feature scaling/normalization
5. Model/parameter initialization
6. Training
7. Prediction
8. Evaluation
9. Required visualization
10. Question-wise execution
