Newb to ML and NNets. What are some ways I could use synaptic to find hidden relationships in standard json objects?

Made a S.O query but doesn't seem very well received 👂
I have a long array of objects that are created to track daily actions.

Example:

[
    {name:'workout', duration:'120', enjoy: true, time:1455063275, tags:['gym', 'weights']},
    {name:'lunch', duration:'45', enjoy: false, time:1455063275, tags:['salad', 'wine']},
    {name:'sleep', duration:'420', enjoy: true, time:1455063275, tags:['bed', 'romance']}
]

I'm having a hard time understanding how to use this data in a neural network to predict if future actions would be enjoyable. Additionally, I want to find hidden relationships between various activities.

Not sure how to get the rubber on the road. How do I feed the network my array of objects and read the results?

If anyone can answer this within the context of https://github.com/cazala/synaptic that would be great. It's also super if the answer is a straight machine learning lesson.

Thanks all!
https://stackoverflow.com/questions/35304800/hidden-relationships-with-javascript-machine-learning