# H&M Personalized Fashion Recommendations — Data

来源：https://www.kaggle.com/competitions/h-and-m-personalized-fashion-recommendations/data

采集时间：2026-10-24T01:29:26Z

For this challenge you are given the purchase history of customers across time, along with supporting metadata. Your challenge is to predict what articles each customer will purchase in the 7-day period immediately after the training data ends.  Customer who did not make any purchase during that time are excluded from the scoring.

## Files

*   **images/** - a folder of images corresponding to each `article_id`; images are placed in subfolders starting with the first three digits of the `article_id`; note, not all `article_id` values have a corresponding image.
*   **articles.csv** - detailed metadata for each `article_id` available for purchase
*   **customers.csv** - metadata for each `customer_id` in dataset
*   **sample_submission.csv** - a sample submission file in the correct format
*   **transactions_train.csv** - the training data, consisting of the purchases each customer for each date, as well as additional information. Duplicate rows correspond to multiple purchases of the same item. Your task is to predict the `article_id`s each customer will purchase during the 7-day period immediately after the training data period.

**NOTE:** You must make predictions for all `customer_id` values found in the sample submission. All customers who made purchases during the test period are scored, regardless of whether they had purchase history in the training data.