In the previous article, we talked a bit about machine learning, performed data augmentation, developed features for the future model and selected the best of them. Now it is time to move on and create a working machine learning model that will learn from our features and trade (hopefully successfully). To evaluate the model, we will write a custom Python tester that will help us evaluate the performance of the model and the beauty of the test graphs. For more beautiful test graphs and greater ...
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