Deployed 983b7ff with MkDocs version: 1.5.3

assets/graph.html

@@ -89,7 +89,7 @@ <h1></h1>
 
                   // parsing and collecting nodes and edges from the python
                   nodes = new vis.DataSet([{"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "NLP Work", "label": "NLP Work", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "https://github.com/zaiquiriw/nlp-portfolio", "label": "https://github.com/zaiquiriw/nlp-portfolio", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "Summary_of_Attention_Article.pdf", "label": "Summary_of_Attention_Article.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "wordnet.pdf", "label": "wordnet.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "ngrams-assignment.pdf", "label": "ngrams-assignment.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "summary.pdf", "label": "summary.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "text-classification.pdf", "label": "text-classification.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "RickMortyTwo.pdf", "label": "RickMortyTwo.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "ML Work", "label": "ML Work", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "nlp overview", "label": "nlp overview", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "data exploration", "label": "data exploration", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "linear regression.pdf", "label": "linear regression.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "linear classification.pdf", "label": "linear classification.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "from scratch.pdf", "label": "from scratch.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "similarities main.pdf", "label": "similarities main.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "similarities regression.pdf", "label": "similarities regression.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "similarities classification.pdf", "label": "similarities classification.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "Clustering.pdf", "label": "Clustering.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "Dimensionality.pdf", "label": "Dimensionality.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "SVM and ensemble.pdf", "label": "SVM and ensemble.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "ClassificationSVM.pdf", "label": "ClassificationSVM.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "RegressionSVM.pdf", "label": "RegressionSVM.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "keras_image_recognition.pdf", "label": "keras_image_recognition.pdf", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "index", "label": "index", "shape": "dot", "size": 10}]);
-                  edges = new vis.DataSet([{"from": "NLP Work", "to": "https://github.com/zaiquiriw/nlp-portfolio", "width": 1}, {"from": "NLP Work", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "NLP Work", "to": "wordnet.pdf", "width": 1}, {"from": "NLP Work", "to": "ngrams-assignment.pdf", "width": 1}, {"from": "NLP Work", "to": "summary.pdf", "width": 1}, {"from": "NLP Work", "to": "text-classification.pdf", "width": 1}, {"from": "NLP Work", "to": "RickMortyTwo.pdf", "width": 1}, {"from": "ML Work", "to": "nlp overview", "width": 1}, {"from": "ML Work", "to": "data exploration", "width": 1}, {"from": "ML Work", "to": "linear regression.pdf", "width": 1}, {"from": "ML Work", "to": "linear classification.pdf", "width": 1}, {"from": "ML Work", "to": "from scratch.pdf", "width": 1}, {"from": "ML Work", "to": "similarities main.pdf", "width": 1}, {"from": "ML Work", "to": "similarities regression.pdf", "width": 1}, {"from": "ML Work", "to": "similarities classification.pdf", "width": 1}, {"from": "ML Work", "to": "Clustering.pdf", "width": 1}, {"from": "ML Work", "to": "Dimensionality.pdf", "width": 1}, {"from": "ML Work", "to": "SVM and ensemble.pdf", "width": 1}, {"from": "ML Work", "to": "ClassificationSVM.pdf", "width": 1}, {"from": "ML Work", "to": "RegressionSVM.pdf", "width": 1}, {"from": "ML Work", "to": "keras_image_recognition.pdf", "width": 1}, {"from": "index", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "index", "to": "keras_image_recognition.pdf", "width": 1}]);
+                  edges = new vis.DataSet([{"from": "NLP Work", "to": "https://github.com/zaiquiriw/nlp-portfolio", "width": 1}, {"from": "NLP Work", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "NLP Work", "to": "wordnet.pdf", "width": 1}, {"from": "NLP Work", "to": "ngrams-assignment.pdf", "width": 1}, {"from": "NLP Work", "to": "summary.pdf", "width": 1}, {"from": "NLP Work", "to": "text-classification.pdf", "width": 1}, {"from": "NLP Work", "to": "RickMortyTwo.pdf", "width": 1}, {"from": "ML Work", "to": "nlp overview", "width": 1}, {"from": "ML Work", "to": "data exploration", "width": 1}, {"from": "ML Work", "to": "linear regression.pdf", "width": 1}, {"from": "ML Work", "to": "linear classification.pdf", "width": 1}, {"from": "ML Work", "to": "from scratch.pdf", "width": 1}, {"from": "ML Work", "to": "similarities main.pdf", "width": 1}, {"from": "ML Work", "to": "similarities regression.pdf", "width": 1}, {"from": "ML Work", "to": "similarities classification.pdf", "width": 1}, {"from": "ML Work", "to": "Clustering.pdf", "width": 1}, {"from": "ML Work", "to": "Dimensionality.pdf", "width": 1}, {"from": "ML Work", "to": "SVM and ensemble.pdf", "width": 1}, {"from": "ML Work", "to": "ClassificationSVM.pdf", "width": 1}, {"from": "ML Work", "to": "RegressionSVM.pdf", "width": 1}, {"from": "ML Work", "to": "keras_image_recognition.pdf", "width": 1}, {"from": "index", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "index", "to": "keras_image_recognition.pdf", "width": 1}, {"from": "index", "to": "ML Work", "width": 1}, {"from": "index", "to": "NLP Work", "width": 1}]);
 
                   nodeColors = {};
                   allNodes = nodes.get({ returnType: "Object" });

index.html

@@ -54,7 +54,7 @@
 <input autocomplete="off" class="md-toggle" data-md-toggle="search" id="__search" type="checkbox"/>
 <label class="md-overlay" for="__drawer"></label>
 <div data-md-component="skip">
-<a class="md-skip" href="#highlights">
+<a class="md-skip" href="#my-projects">
           Skip to content
         </a>
 </div>
@@ -197,8 +197,8 @@
     </label>
 <ul class="md-nav__list" data-md-component="toc" data-md-scrollfix="">
 <li class="md-nav__item">
-<a class="md-nav__link" href="#highlights">
-    Highlights
+<a class="md-nav__link" href="#my-projects">
+    My Projects
   </a>
 </li>
 </ul>
@@ -233,8 +233,8 @@
     </label>
 <ul class="md-nav__list" data-md-component="toc" data-md-scrollfix="">
 <li class="md-nav__item">
-<a class="md-nav__link" href="#highlights">
-    Highlights
+<a class="md-nav__link" href="#my-projects">
+    My Projects
   </a>
 </li>
 </ul>
@@ -277,9 +277,11 @@ <h1>Howdy There!</h1>
 <p>My academic journey in Computer Science was transformative, but it was my focus on machine learning that truly shaped my passion and expertise. The hands-on experience I gained has fueled my desire to continue learning and growing in the field of data science.</p>
 <p>Influenced by my professor, who transitioned from industry to academia, I too am considering a similar path. I believe that real-world experience can provide invaluable insights that can be brought back into academic or research settings.</p>
 <p>Feel free to explore my projects and reach out if you have any questions or opportunities that align with my interests.</p>
-<h3 id="highlights">Highlights<a class="headerlink" href="#highlights" title="Permanent link">¶</a></h3>
+<h3 id="my-projects">My Projects<a class="headerlink" href="#my-projects" title="Permanent link">¶</a></h3>
 <p>Out of my different projects, I’m most proud of the work I did researching <a href="Summary_of_Attention_Article.pdf" title="explainability in attention based models">explainability in attention based models</a> and fine tuning Google’s MobileNetV2 for <a href="keras_image_recognition.pdf" title="identifying grains of rice">identifying grains of rice</a>.</p>
 <p><a class="glightbox" data-desc-position="bottom" data-height="auto" data-type="image" data-width="100%" href="assets/img/Pasted%20image%2020231029141843.png"><img alt="Pasted image 20231029141843.png" src="assets/img/Pasted%20image%2020231029141843.png" title="Pasted image 20231029141843.png"/></a></p>
+<p>You can view all of my introduction to <a href="ML%20Work/" title="machine learning">machine learning</a> work as well as my <a href="NLP%20Work/" title="natural language processing">natural language processing</a> work as pdfs here, or look at the source on <a href="https://github.com/zaiquiriw">github</a>.</p>
+<p>I can’t wait to do more projects and add more experince to this site!</p>
 <!-- Source file information -->
 <!-- taken from 
 https://github.com/squidfunk/mkdocs-material/blob/master/src/partials/source-file.html -->