[D] tutorial on how to build streaming ML applications

My primary expertise is audio processing, but i believe this task happens in other domains too: running a model on chunks of infinitely long input. while for some architectures it is straightforward, it can get tedious for convolutional nets. I put together a comprehensive tutorial how to build a streaming ML applications: [https://balacoon.com/blog/streaming\_inference/](https://balacoon.com/blog/streaming_inference/). would be curious to learn wether its a common problem and how do people usually deal with it. because generally resources on the topic are surprisingly scarce.

machinelearning