Now lets try decimal (float) inputs and outputs. For every X value we train the Neural Network on y = 2X + 3 (or any other equation for that matter)

I have made the Keras model.fit a bit simpler than the Web App below. This model has no gradceful exit Class, but is easier to understand.

For this example we will test the data on x = 5.32 which should provide a y close to 13.64

For more flexible testing see the web App below

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Now lets try the above in a full Machine Learning Web App

Tensorflowjs Machine Learning Web App Template

As simple as possible template. Note that for simplicity this has minimal CSS

Pre-Set Values:

Learning Rate:
Samples per batch:
Epochs: (# of batches to run)
Validation Split :

Data:

xTrainingData:	1.20, 2.10, 3.40, 4.20
yTrainingTarget:	5.40, 7.20, 9.80, 11.40

Multiplier for the Random Generate Note: "Samples per Batch" above effects the generator

Compile or Load Model:

Compile, Train, Test:			Import / Export
Compile Model:
Train Model:		Epochs run:
Test Trained Model with New Data:	New Data:	5.32		Shape:

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