Trying to detect recurring events at certain intervals, e.g. daily, weeekly, monthly, annually I don't have much experience with ML but am looking for some guidance on where I should start.  

I have timestamp data mapped to a certain category, e.g. travel, food, groceries, etc.

Judging by some other posts and answers, would it be correct to break the data into these intervals (day, week, month, year) and then try to detect patterns across the intervals?  Are there any particular approaches or algorithms I should investigate first?  Thanks!
Given an event type and a sequence of times at which it has occurred, there are several ways to check whether it seems to recur periodically.

One simple approach is to look at the interarrival times (the time between each occurrence and the previous occurrence), and histogram those; if it is periodic, you'll see a sharp peak in the histogram.

Another approach is to use autocorrelation to detect periodicity.  See, e.g., https://en.wikipedia.org/wiki/Autocorrelation.  The Fourier transform can be useful here.