Update headings and punctuation in sycamore page (opensearch-project#…

…8301)

* Update sycamore.md

Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

* Update _tools/sycamore.md

Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>

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Signed-off-by: kolchfa-aws <105444904+kolchfa-aws@users.noreply.github.com>
Signed-off-by: Noah Staveley <noah.staveley@intel.com>

_tools/sycamore.md

@@ -11,23 +11,23 @@ has_children: false
 
 To get started, visit the [Sycamore documentation](https://sycamore.readthedocs.io/en/stable/sycamore/get_started.html).
 
-# Sycamore ETL pipeline structure
+## Sycamore ETL pipeline structure
 
 A Sycamore extract, transform, load (ETL) pipeline applies a series of transformations to a [DocSet](https://sycamore.readthedocs.io/en/stable/sycamore/get_started/concepts.html#docsets), which is a collection of documents and their constituent elements (for example, tables, blocks of text, or headers). At the end of the pipeline, the DocSet is loaded into OpenSearch vector and keyword indexes.
 
 A typical pipeline for preparing unstructured data for vector or hybrid search in OpenSearch consists of the following steps:
 
 * Read documents into a [DocSet](https://sycamore.readthedocs.io/en/stable/sycamore/get_started/concepts.html#docsets).
 * [Partition documents](https://sycamore.readthedocs.io/en/stable/sycamore/transforms/partition.html) into structured JSON elements.
-* Extract metadata, filter, and clean data using [transforms](https://sycamore.readthedocs.io/en/stable/sycamore/APIs/docset.html).
+* Extract metadata and filter and clean data using [transforms](https://sycamore.readthedocs.io/en/stable/sycamore/APIs/docset.html).
 * Create [chunks](https://sycamore.readthedocs.io/en/stable/sycamore/transforms/merge.html) from groups of elements.
 * Embed the chunks using the model of your choice.
 * [Load](https://sycamore.readthedocs.io/en/stable/sycamore/connectors/opensearch.html) the embeddings, metadata, and text into OpenSearch vector and keyword indexes.
 
 For an example pipeline that uses this workflow, see [this notebook](https://github.com/aryn-ai/sycamore/blob/main/notebooks/opensearch_docs_etl.ipynb).
 
 
-# Install Sycamore
+## Install Sycamore
 
 We recommend installing the Sycamore library using `pip`. The connector for OpenSearch can be specified and installed using extras. For example:
 
@@ -45,4 +45,4 @@ pip install sycamore-ai[opensearch,local-inference]
 
 ## Next steps
 
-For more information, visit the [Sycamore documentation](https://sycamore.readthedocs.io/en/stable/sycamore/get_started.html).
+For more information, visit the [Sycamore documentation](https://sycamore.readthedocs.io/en/stable/sycamore/get_started.html).