+If you want to create custom models, there is the easy way, and the longer but more flexible way. The easy way is to use [teachablemachine](https://teachablemachine.withgoogle.com/train/image), which I have done in this repo for the dogs-vs-cats model. This is limited to image classification but is very straightforward. The longer way allows you to use any neural network architecture to produce a tensorflow model, which you then convert to a tflite model. An example of this approch is described in [this article](https://towardsdatascience.com/inferences-from-a-tf-lite-model-transfer-learning-on-a-pre-trained-model-e16e7c5f0ee6), or jump straight [to the code](https://github.com/arshren/TFLite/blob/master/Transfer%20Learning%20with%20TFLite-Copy1.ipynb).
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