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C19 Update with Italy + TensorFlow World NN

Source info:

Author: Prof. Christopher L. Liner
Date: 2020-06-27 18:04:00
Blog: Seismos
URL: http://seismosblog.blogspot.com/2020/06/c19-update-with-italy-tensorflow-world.html

Summary:

2020-06-27 Total US C19 deaths 125,039 Last five daily = [ 423  829  754 2425  629] Future estimates    124824 +/- 1912  =  Jul 1 total (95% confidence)    134802 +/- 1912  =  Aug 1    139836 +/- 1912  =  Sep 1 Total world C19 deaths 494,181 Last five daily = [3588 5416 5171 6554 4869] Future estimates    491466 +/- 178878  =  Jul 1 total (95% confidence)    578344 +/- 178878  =  Aug 1    645159 +/- 178878  =  Sep 1 Total Italy C19 deaths 34,708 Last five daily = [ 23  18 -31  34  30] Future estimates    34903 +/- 109  =  Jul 1 total (95% confidence)    35365 +/- 109  =  Aug 1    35513 +/- 109  =  Sep 1 Total Arkansas C19 deaths 249 Last five daily = [ 2 10  3  0  9] New neural network implementation is presented today. This uses Keras and TensorFlow. The model architecture is given below the figure. In this version the input data is split into a randomly selected training part (80%) and a testing, or validation, part (20%). The lower plot shows computed error against the train and validate data at each training pass (epoch). We see the error reducing similarly for the train and validate data, which is good. If the train error is much lower than the validate error the data is being overfit because there are too many parameters in the model.  Our error behavior looks fine, but it is quite possible that a simpler network (fewer hidden layers and neurons per layer) would produce similar results. After all, before today we were fitting the data using 15 neurons in one hidden layer, a total of 48 trainable parameters. Amazing it worked as well as it did. Predictions for world daily C19 deaths from this NN 4343  =  Jul 1 daily (day 161) 4302  =  Aug 1 daily (day 192) 4378  =  Sep 1 daily (day 223)   Model: "sequential" ____________________________________________ Layer (type)                 Output Shape              Param #    ======================================= dense (Dense)                (None, 1)                 2          ____________________________________________ dense_1 (Dense)              (None, 64)                128        ____________________________________________ dense_2 (Dense)              (None, 64)                4160       ____________________________________________ dense_3 (Dense)              (None, 64)                4160       ____________________________________________ dense_4 (Dense)              (None, 64)                4160       _____________________________________________ dense_5 (Dense)              (None, 64)                4160       _____________________________________________ dense_6 (Dense)              (None, 1)                 65         ======================================== Total params: 16,835 Trainable params: 16,835 Non-trainable params: 0

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Keywords:

Covid-19

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