WeightliftingApp ML Model

A series of programs written in Python using Weightling App data to train a Keras deep learning model for the purpose of workout type prediction based on the exercises performed.

Body split training input example:

"2 Abs / Core#3 Biceps#2 Triceps" becomes [ 2 0 3 0 0 0 0 0 2 ] :

Abs / Core	back	Biceps	cardio	chest	legs	Olympic	shoulders	Triceps
2	0	3	0	0	0	0	0	2

Categorical expected output example:

"arms" becomes [ 0 1 0 0 0 0 0 0 0 0 0 0 ] :

abs	arms	back	cardio	chest	legs	shoulders	push	pull	chestBack	chestBiceps	fullBody
0	1	0	0	0	0	0	0	0	0	0	0

      ||||||||
      ||||||||
      ||||||||
  Processed by model
    \\\\\\//////
      \\\\////
        \\//

Categorical actual output example:

[ .003 .981 .001 .002 .000 .000 .000 .000 .000 .000 .012 .001 ] becomes "arms" :

abs	arms	back	cardio	chest	legs	shoulders	push	pull	chestBack	chestBiceps	fullBody
.003	.981	.001	.002	.000	.000	.000	.000	.000	.000	.012	.001

Current accuracy (744 training points @ 100,000 epochs, categorical crossentropy):

• Training data: 100.0% 👍
• Test data: 97.0% 👍

Current model