You are an ML engineer at a large grocery retailer with stores in multiple regions. You have been asked to create an inventory prediction model. Your models features include region, location, historical demand, and seasonal popularity. You want the algorithm to learn from new inventory data on a daily basis.
Which algorithms should you use to build the model?
A . Classification
B . Reinforcement Learning
C . Recurrent Neural Networks (RNN)
D . Convolutional Neural Networks (CNN)
Answer: C
Explanation:
"algorithm to learn from new inventory data on a daily basis" = time series model, best option to deal with time series is forsure RNN
https://builtin.com/data-science/recurrent-neural-networks-and-lstm
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