Update data_performance.ipynb

Author: RenuPatelGoogle

site/en/guide/data_performance.ipynb

@@ -713,12 +713,12 @@
         "Here is a summary of the best practices for designing performant TensorFlow\n",
         "input pipelines:\n",
         "\n",
-        "*   [\Use the `prefetch` transformation\](#prefetching) to overlap the work of a producer and consumer\n",
-        "*   [\Parallelize the data reading transformation\](#parallelizing_data_extraction) using the `interleave` transformation\n",
-        "*   [\Parallelize the `map` transformation\](#parallelizing_data_transformation) by setting the `num_parallel_calls` argument\n",
-        "*   [\Use the `cache` transformation\](#caching) to cache data in memory during the first epoch\n",
-        "*   [\Vectorize user-defined functions\](#vectorizing_mapping) passed in to the `map` transformation\n",
-        "*   [\Reduce memory usage\](#reducing_memory_footprint) when applying the `interleave`, `prefetch`, and `shuffle` transformations"
+        "*   [Use the `prefetch` transformation](#prefetching) to overlap the work of a producer and consumer\n",
+        "*   [Parallelize the data reading transformation](#parallelizing_data_extraction) using the `interleave` transformation\n",
+        "*   [Parallelize the `map` transformation](#parallelizing_data_transformation) by setting the `num_parallel_calls` argument\n",
+        "*   [Use the `cache` transformation](#caching) to cache data in memory during the first epoch\n",
+        "*   [Vectorize user-defined functions](#vectorizing_mapping) passed in to the `map` transformation\n",
+        "*   [Reduce memory usage](#reducing_memory_footprint) when applying the `interleave`, `prefetch`, and `shuffle` transformations"
       ]
     },
     {