reworded "data-frame" --> features dict.

samples/core/tutorials/estimators/linear.ipynb

@@ -623,7 +623,7 @@
         "\n",
         "Estimators use a system called [feature columns](https://www.tensorflow.org/guide/feature_columns) to describe how the model should interpret each of the raw input features. An Estimator expects a vector of numeric inputs, and feature columns describe how the model should convert each feature.\n",
         "\n",
-        "Selecting and crafting the right set of feature columns is key to learning an effective model. A *feature column* can be either one of the raw columns in the original data frame (a *base feature column*), or any new columns created using transformations defined over one or multiple base columns (a *derived feature columns*).\n",
+        "Selecting and crafting the right set of feature columns is key to learning an effective model. A *feature column* can be either one of the raw inputs in the original features `dict` (a *base feature column*), or any new columns created using transformations defined over one or multiple base columns (a *derived feature columns*).\n",
         "\n",
         "A feature column is an abstract concept of any raw or derived variable that can be used to predict the target label."
       ]
@@ -1401,4 +1401,4 @@
       ]
     }
   ]
-}
\ No newline at end of file
+}