"if we simply numerically encode (label encode or `le`) the values, starting from 1 (we will save 0 for padding, i.e. unseen values)"
"if we simply numerically encode (label encode or `le`) the values:"
]
},
{
...
...
@@ -146,7 +146,9 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"now, let's see if the two implementations are equivalent"
"Note that in the functioning implementation of the package we start from 1, saving 0 for padding, i.e. unseen values. \n",
"\n",
"Now, let's see if the two implementations are equivalent"
]
},
{
...
...
@@ -261,7 +263,7 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"Note that even though the input dim is 10, the Embedding layer has 11 weights. This is because we save 0 for padding, which is used for unseen values during the encoding process"
"Note that even though the input dim is 10, the Embedding layer has 11 weights. Again, this is because we save 0 for padding, which is used for unseen values during the encoding process"
"Also mentioning that one could build a model with the individual components independently. For example, a model comprised only by the `wide` component would be simply a linear model. This could be attained by just:"
