Say I have a training dataset composed by 128 1-Dimensional time series in form of numpy arrays.
They all correspond to a certain action that I label
action_1 and I want to recognize.
What would be the most efficient way to accomplish the following taks:
- Train a model with the training dataset (the 128 1-D numpy arrays)
- Ask the model to predict the action in a new test entry (a 1-D numpy array)
This is my very first attempt at Machine Learning, thank you in advance for any indications.