How can I perform multivariable regression with neural networks?

I want to use a neural network to perform a multivariable regression, where my dataset contains multiple features, but I can't for the life of me figure it out. Every kind of tutorial on the internet seems to be either for a single feature without information on how to upgrade it to multiple, or results in a yes or a no when I need numeric predictions (that is, it uses neural networks for classification).

Can someone please recommend some kind of resource I can use to learn this?

Have a look at sklearn's sklearn.neural_network.MLPRegressor class, which uses a multi-layer neural network to do regression. You first need to define the object MLPRegressor, for example, by specifying the value of the parameter hidden_layer_sizes, which determines the number of layers and the number of neurons per layer, then you should call the method fit on this created object and pass to it your data matrix $$X \in \mathbb{R}^{n \times m}$$, where $$n$$ is the number of samples and $$m$$ is the number of features.