mindwrapped/collaborative-filtering-movielens-copyai分析软件

Model description

This repo contains the model and the notebook on how to build and train a Keras百度流畅ai制作 model for Collaborative Filtering for Movie Recommendations.

Full credits to Siddhartha Banerjee.百度流畅ai制作

Intended uses & limitations

Based on a user and movies they have rated highly in the past, this model outputs the predicted rating a user would give to a movie they haven’t seen yet (between 0-1). This information can be used to find out the top recommended movies for this user.al一键脱装入口

Training and evaluation data

The dataset consists of user’s ratings on specific movies. It also consists of the movie’s specific genres.ima是什么软件

Training procedure

The model was trained for 5 epochs with a batch size of 64.grok中文版下载

Training hyperparameters

The following hyperparameters were used during training:免费的ai工具

• optimizer: {‘name’: ‘Adam’, ‘learning_rate’: 0.001, ‘decay’: 0.0, ‘beta_1’: 0.9, ‘beta_2’: 0.999, ‘epsilon’: 1e-07, ‘amsgrad’: False}
• training_precision: float32

Training Metrics

Model Plot