Recommender Systems: An Applied Approach using Deep Learning - Random Train-Test Split

The video tutorial explains how to perform a train-test split using TensorFlow. It begins with an introduction to the concept of train-test split and the importance of randomness. The instructor demonstrates setting a random seed for reproducibility and shuffling the dataset. The shuffled data is then split into training and testing sets, ensuring randomness to improve model results. The tutorial concludes with a brief mention of moving on to model development in the next video.

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