---
tags:
- keras
- time-series-classification
- education
---

# Wearable Activity Classifier – Group ___

## Task
Classify a 100-step, one-feature sensor sequence into **Stationary**, **Walking**, or **Running**.

## Model selected
- Architecture: [CNN / SimpleRNN / LSTM / CNN+LSTM]
- Input shape: `(100, 1)`
- Output classes: 3
- Parameters: ______

## Training data
Synthetic signals generated in the class notebook. The dataset was designed for teaching and is not a real wearable benchmark.

## Evaluation
- Test accuracy: ______
- Training time in our run: ______ seconds

## Why we selected this model
[Write 2–4 sentences using evidence from your comparison.]

## Limitations
- Synthetic, simplified data
- One sensor feature only
- No testing across real users/devices
- Not intended for health, safety, or production use

## Team learning note
[State one thing your group learned by comparing CNN, RNN, and LSTM.]