I grew up in a household where the inevitability of death was a strangely common motivator. We were told, as 10 year olds, to exercise because it would help us live longer. Bad habits were frequently flagged as sources of death. Statements about our future were usually conditioned by “if you live that long.” It …
One of the more exciting new features coming soon to AutoTS is the automatic detection of holidays. That’s exactly what it sounds like: figuring out when holidays are occurring and being able to generate that calendar for the future. Firstly, why is this needed? A couple of reasons. The big reason is that holidays are …
It has been impossible in the past to get all three of the largest neural network architectures running in the same Python environment in such a way that they don’t conflict and so that they will also train on GPU. The reason I want all the libraries running in the same environment is that AutoTS …
PyTorch, Tensorflow, and MXNet on GPU in the same environment and GPU vs CPU performance Read More »
Note that a variation on this article may also be posted on the Nousot blog. Time series are a string of numbers varying across time. It could be the weather, sales of tissue paper, electricity demand of a region, or countless other things. There are plenty of useful things to do with this type of …
While doing some benchmarking of my AutoTS package I quickly discovered a troubling trend – my newest, fanciest, most expensive Intel i7 CPUs – an Intel 10700 and 1165G7, were performing vastly slower than their older counterparts. I wasn’t terribly surprised to see the 1165G7 having issues: Tiger Lake – a brand new architecture CPU …
For loops are very convenient. With a combination of a for loop and some if-else statements you can do just about anything. There’s just one problem though, for loops are kinda slow. There are many ways to speed up the code, the best usually, in the data science world, to use vectorized NumPy or Pandas …
AutoTS development has been on hold for the last three months or so. Partly that is because it finally works more or less as I originally intended. In fact, it works better than I originally intended. Still, the current development feels like a failure as I failed to use it to submit any decent models …
This release represents several months of fairly hard work for me. It even has a pretty, if simple documentation website that you can check out here. It features quite a number of bug fixes, including several rather critical ones that fixed cross validation not actually cross validating. As always, my biggest focus was on data …
As part of my time series forecasting package, I have invented my own algorithm. Which sounds really cool, but in reality isn’t that special. The reason it isn’t that special is it is just a combination of existing ideas applied together to this specific domain. On the positive side, the method isn’t really that difficult …
I have a history of obsessing over predicting the future. Probably the first major time series project I had was in grad school, with a consulting project forecasting amusement park attendance that ultimately found a LSTM network to be most effective. Again at my first data science job, forecasting demand and sales and prices. Probably …
