# "Crack the Code — Data

来源：https://www.kaggle.com/competitions/crack-the-code/data

本地 Meta Kaggle 快照；不是本次实时页面。

# Dataset Description

### 📁 *Dataset Description*

The competition uses the *MNIST (Modified National Institute of Standards and Technology)* dataset—one of the most well-known datasets in the field of machine learning and computer vision.

It contains *70,000 grayscale images* of handwritten digits from *0 to 9, each sized **28x28 pixels*.

#### 📦 Dataset Split
- *Training Set*: 60,000 images with labels (used to train your model).
- *Test Set*: 10,000 images without labels (used for evaluation).

#### 🖼 Image Format
- Each image is a *28x28 pixel grayscale image*, flattened into a 784-length vector in CSV format or as .png images depending on the dataset version used.
- Pixel values range from *0 (black)* to *255 (white)*.

#### 🧾 File Format (CSV)
If provided in CSV format, the files are structured as follows:

##### ✅ train.csv
| label | pixel0 | pixel1 | pixel2 | ... | pixel783 |
|-------|--------|--------|--------|-----|----------|
| 5     | 0      | 0      | 12     | ... | 0        |

- *label*: The correct digit (0 to 9).
- *pixel0 to pixel783*: Grayscale values of each pixel.

##### ❓ test.csv
| pixel0 | pixel1 | pixel2 | ... | pixel783 |
|--------|--------|--------|-----|----------|
| 0      | 0      | 12     | ... | 0        |

- *No label column* in test data. Your task is to predict the missing labels and submit them in the submission.csv.

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