How to work with input which is a combination of metadata+ vectorized text data + image pixel data to build a Regression Model (predict views)?
If we avoid a Neural Network,

You should reduce the dimensionality of images e.g. PCA [ Assuming no translational variance among images]
Can try the same for the other two datasets with 50 features
Then try the ML models

If that doesn't work, we may try CNN for the image data.
In that scenario, we will need a mixed architecture of simple Neural Network and CNN.

Check this Paper
Blog on the paper