"Note: Hash collisions are unavoidable, but often have minimal impact on model quiality. The effeect may be noticable if the hash buckets are being used to compress the input space. See [this notebook](https://colab.research.google.com/github/tensorflow/models/blob/master/samples/outreach/blogs/housing_prices.ipynb) for a more visual example of the effect of these hash collisions.\n",
"Note: Hash collisions are unavoidable, but often have minimal impact on model quiality. The effect may be noticable if the hash buckets are being used to compress the input space. See [this notebook](https://colab.research.google.com/github/tensorflow/models/blob/master/samples/outreach/blogs/housing_prices.ipynb) for a more visual example of the effect of these hash collisions.\n",
"\n",
"No matter how we choose to define a `SparseColumn`, each feature string is mapped into an integer ID by looking up a fixed mapping or by hashing. Under the hood, the `LinearModel` class is responsible for managing the mapping and creating `tf.Variable` to store the model parameters (model *weights*) for each feature ID. The model parameters are learned through the model training process described later.\n",