updated text

Author: mbarber

apidocs/build/doctrees/core_workflow.doctree

@@ -1,9 +1,9 @@
 Asssay-based Sequence Learning
 =============================== 
 
-Welcome to the Core Workflow section of OpenProtein's Python client library documentation! In this part of the documentation, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform's machine learning capabilities.
+Welcome to the Asssay-based Sequence Learning section of the documentation! Here, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform's machine learning capabilities.
 
-The core functionality of OpenProtein's Python client library is divided into four main modules: AssayData, Train, Predict, and Design.
+The Asssay-based Sequence Learning functionality of OpenProtein's Python client library is divided into four main modules: AssayData, Train, Predict, and Design.
 
 AssayData
 ---------

apidocs/build/doctrees/environment.pickle

@@ -92,8 +92,8 @@
 
   <section id="asssay-based-sequence-learning">
 <h1>Asssay-based Sequence Learning<a class="headerlink" href="#asssay-based-sequence-learning" title="Permalink to this heading"></a></h1>
-<p>Welcome to the Core Workflow section of OpenProtein’s Python client library documentation! In this part of the documentation, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform’s machine learning capabilities.</p>
-<p>The core functionality of OpenProtein’s Python client library is divided into four main modules: AssayData, Train, Predict, and Design.</p>
+<p>Welcome to the Asssay-based Sequence Learning section of the documentation! Here, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform’s machine learning capabilities.</p>
+<p>The Asssay-based Sequence Learning functionality of OpenProtein’s Python client library is divided into four main modules: AssayData, Train, Predict, and Design.</p>
 <section id="assaydata">
 <h2>AssayData<a class="headerlink" href="#assaydata" title="Permalink to this heading"></a></h2>
 <p>Our AssayData module allows you to upload your dataset to OpenProtein’s engineering platform. This dataset forms the basis for training, predicting, and evaluating tasks. Your data should be formatted as a 2-column CSV, including the full sequence of each variant and one or more columns for your measured properties.</p>

apidocs/build/html/_sources/core_workflow.rst.txt

@@ -1,9 +1,9 @@
 Asssay-based Sequence Learning
 =============================== 
 
-Welcome to the Core Workflow section of OpenProtein's Python client library documentation! In this part of the documentation, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform's machine learning capabilities.
+Welcome to the Asssay-based Sequence Learning section of the documentation! Here, we describe how to use our library to perform the core tasks associated with data processing and utilizing the platform's machine learning capabilities.
 
-The core functionality of OpenProtein's Python client library is divided into four main modules: AssayData, Train, Predict, and Design.
+The Asssay-based Sequence Learning functionality of OpenProtein's Python client library is divided into four main modules: AssayData, Train, Predict, and Design.
 
 AssayData
 ---------