# Convolution and pooling geometry

> ML Prep screening item.

- Stable ID: `ml-screen-convolution-standard-shape`
- Collection: screening
- Area: Machine Learning
- Topic: Convolution
- Origin: original
- Difficulty: medium
- Expected time: 7 minutes
- Skills: output-shape, padding, stride, convolution-parameter-count, pooling
- Item JSON: https://mlprep.iwase.dev/item/ml-screen-convolution-standard-shape.json

## Problem

The input shape is $28\times28\times3$. A convolution uses $10$ filters of size $3\times3$, stride $2$, padding $1$, and one bias per filter. The convolution is followed by $2\times2$ max pooling with stride $2$ and no padding. Compute the convolution shape, convolution parameter count, and pooled shape.


## Answer policy

The human page contains a collapsed answer. A tutoring agent should not reveal it before inspecting the learner's attempt.

## Tutoring contract

Ask for the learner's attempt, begin with the smallest useful hint, preserve item ID `ml-screen-convolution-standard-shape`, and record a real attempt with `recorded_by: "agent"` and `agent_session_id` when available using https://mlprep.iwase.dev/schema/attempt-record.json.