Recommender Systems: An Applied Approach using Deep Learning - Accuracy Versus Recommendations

The video tutorial demonstrates how to plot and analyze the accuracy of top 100 and top 10 recommendations using Python's plotting library. It covers setting up the plot, calculating validation runs, and epochs, and then plotting both validation and training accuracies for top 100 and top 10 recommendations. The tutorial concludes with finalizing the plot with appropriate titles and labels, and analyzing the results to understand the model's performance.

What is the purpose of using the numpy line space command in this context?

Describe the steps taken to plot the training part for top 10 recommendations.

How does the text suggest making predictions based on the model's performance?