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Author: MarkusRosen

ReadMe.md

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+# Creating a map and KDE plot of points and polygons with Python
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+![Input image.](teaser.png)
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+One of the most significant advantages of artificial deep neural networks has always been that they can pretty much take any kind of data as input and can approximate a non-linear function to predict on that data. I have been searching for online tutorials to create a neural network that takes tabular and image data as inputs and predicts a single value as output. So far, I have not found any start to end tutorials that implement such a network in PyTorch. Therefore I decided to tackle this question on my own. So in this tutorial, I will show you how you can use `PyTorch Lightning` to predict real estate prices of houses through matching image data and tabular information. [You can find the sample data sets used here](<[here](https://1drv.ms/u/s!AqUPqx8G81xZiL1l80RtZbjPj43MhA?e=KagzKc)>). The full tutorial is available through my [blog](https://rosenfelder.ai/multi-input-neural-networ-pytorch/).