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View Code? Open in Web Editor NEW:running_shirt_with_sash: Fashion Recommender System
:running_shirt_with_sash: Fashion Recommender System
1 - Format data entry to the model
2 - Implement the neural network
3 - Implement the train policy
4 - Execute and get results from the method
Just make LightGCN terminate the test phase fast. Now he can take 16 hours + in this phase, we need it to run more fast.
The simplest solution i think is to do a parallelism in this phase.
Stacked methods: Popular and NCF
1 - Split base in train and validation to train the stacking method (cross validation if possible)
2 - Train the method using the splitted data
3 - Use any simple meta-learner, it can be a linear regression or a tree based method (like random forest)
4 - Train stacked methods with original training dataset
5 - Execute it and get results
Find the best popularity method that can obtain same results in the challenge
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