| @@ -4,6 +4,17 @@ This is an implementation of WideDeep as described in the [Wide & Deep Learning | |||||
| WideDeep model jointly trained wide linear models and deep neural network, which combined the benefits of memorization and generalization for recommender systems. | WideDeep model jointly trained wide linear models and deep neural network, which combined the benefits of memorization and generalization for recommender systems. | ||||
| ## Requirements | |||||
| - Install [MindSpore](https://www.mindspore.cn/install/en). | |||||
| - Download the dataset and convert the dataset to mindrecord, command as follows: | |||||
| ``` | |||||
| python src/preprocess_data.py | |||||
| ``` | |||||
| Arguments: | |||||
| * `--data_path`: Dataset storage path (Default: ./criteo_data/). | |||||
| ## Dataset | ## Dataset | ||||
| The Criteo datasets are used for model training and evaluation. | The Criteo datasets are used for model training and evaluation. | ||||