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zaiquiriw · Oct 29, 2023 · 28e87e1 · 28e87e1
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diff --git a/docs/ML Work/ClassificationSVM.pdf → docs/ClassificationSVM.pdf b/docs/ML Work/ClassificationSVM.pdf → docs/ClassificationSVM.pdf
diff --git a/docs/ML Work/Clustering.pdf → docs/Clustering.pdf b/docs/ML Work/Clustering.pdf → docs/Clustering.pdf
diff --git a/docs/ML Work/Dimensionality.pdf → docs/Dimensionality.pdf b/docs/ML Work/Dimensionality.pdf → docs/Dimensionality.pdf
diff --git a/docs/ML Work/index.md → docs/ML Work.md b/docs/ML Work/index.md → docs/ML Work.md
diff --git a/docs/NLP Work/index.md → docs/NLP Work.md b/docs/NLP Work/index.md → docs/NLP Work.md
diff --git a/docs/ML Work/RegressionSVM.pdf → docs/RegressionSVM.pdf b/docs/ML Work/RegressionSVM.pdf → docs/RegressionSVM.pdf
diff --git a/docs/NLP Work/RickMortyTwo.pdf → docs/RickMortyTwo.pdf b/docs/NLP Work/RickMortyTwo.pdf → docs/RickMortyTwo.pdf
diff --git a/docs/ML Work/SVM and ensemble.pdf → docs/SVM and ensemble.pdf b/docs/ML Work/SVM and ensemble.pdf → docs/SVM and ensemble.pdf
diff --git a/...NLP Work/Summary_of_Attention_Article.pdf → docs/Summary_of_Attention_Article.pdf b/...NLP Work/Summary_of_Attention_Article.pdf → docs/Summary_of_Attention_Article.pdf
diff --git a/docs/assets/css/customization.css b/docs/assets/css/customization.css
@@ -6,6 +6,26 @@ DONT FORGET TO EDIT THE URL
 }
 */
 
+[data-md-color-scheme="zaiq-light"] {
+    --md-primary-fg-color:        #3c3836;
+    --md-primary-bg-color:        #fbf1c7;
+
+    --md-accent-fg-color:                ;
+    --md-accent-fg-color--transparent:   ;
+    --md-accent-bg-color:                ;
+    --md-accent-bg-color--light:         ;
+}
+
+[data-md-color-scheme="zaiq-dark"] {
+    --md-primary-fg-color:               #ebdbb2;
+    --md-primary-bg-color:               #282828;
+
+    --md-accent-fg-color:                #ebdbb2;
+    --md-accent-fg-color--transparent:   #ebdbb2;
+    --md-accent-bg-color:                #ebdbb2;
+    --md-accent-bg-color--light:         #ebdbb2;
+}
+
 .md-typeset details.wiki,
 .md-typeset .admonition.wiki {
     border-color: transparent;

diff --git a/docs/assets/graph.html b/docs/assets/graph.html
@@ -88,8 +88,8 @@ <h1></h1>
 
 
                   // parsing and collecting nodes and edges from the python
-                  nodes = new vis.DataSet([{"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "copart internship", "label": "copart internship", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "portfolio cleanup", "label": "portfolio cleanup", "shape": "dot", "size": 10}, {"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "NLP Work/index", "label": "NLP Work/index", "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/index", "label": "ML Work/index", "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": "copart internship", "to": "portfolio cleanup", "width": 1}, {"from": "NLP Work/index", "to": "https://github.com/zaiquiriw/nlp-portfolio", "width": 1}, {"from": "NLP Work/index", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "NLP Work/index", "to": "wordnet.pdf", "width": 1}, {"from": "NLP Work/index", "to": "ngrams-assignment.pdf", "width": 1}, {"from": "NLP Work/index", "to": "summary.pdf", "width": 1}, {"from": "NLP Work/index", "to": "text-classification.pdf", "width": 1}, {"from": "NLP Work/index", "to": "RickMortyTwo.pdf", "width": 1}, {"from": "ML Work/index", "to": "nlp overview", "width": 1}, {"from": "ML Work/index", "to": "data exploration", "width": 1}, {"from": "ML Work/index", "to": "linear regression.pdf", "width": 1}, {"from": "ML Work/index", "to": "linear classification.pdf", "width": 1}, {"from": "ML Work/index", "to": "from scratch.pdf", "width": 1}, {"from": "ML Work/index", "to": "similarities main.pdf", "width": 1}, {"from": "ML Work/index", "to": "similarities regression.pdf", "width": 1}, {"from": "ML Work/index", "to": "similarities classification.pdf", "width": 1}, {"from": "ML Work/index", "to": "Clustering.pdf", "width": 1}, {"from": "ML Work/index", "to": "Dimensionality.pdf", "width": 1}, {"from": "ML Work/index", "to": "SVM and ensemble.pdf", "width": 1}, {"from": "ML Work/index", "to": "ClassificationSVM.pdf", "width": 1}, {"from": "ML Work/index", "to": "RegressionSVM.pdf", "width": 1}, {"from": "ML Work/index", "to": "keras_image_recognition.pdf", "width": 1}]);
+                  nodes = new vis.DataSet([{"color": "#97c2fc", "font": {"color": "#7c7c7c"}, "id": "index", "label": "index", "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": "keras_image_recognition.pdf", "label": "keras_image_recognition.pdf", "shape": "dot", "size": 10}, {"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": "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}]);
+                  edges = new vis.DataSet([{"from": "index", "to": "Summary_of_Attention_Article.pdf", "width": 1}, {"from": "index", "to": "keras_image_recognition.pdf", "width": 1}, {"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}]);
 
                   nodeColors = {};
                   allNodes = nodes.get({ returnType: "Object" });

diff --git a/docs/assets/img/.push b/docs/assets/img/.push
diff --git a/docs/assets/img/Pasted image 20231029141843.png b/docs/assets/img/Pasted image 20231029141843.png
diff --git a/docs/ML Work/from scratch.pdf → docs/from scratch.pdf b/docs/ML Work/from scratch.pdf → docs/from scratch.pdf
diff --git a/...ork/hugging-face.ipynb - Colaboratory.pdf → docs/hugging-face.ipynb - Colaboratory.pdf b/...ork/hugging-face.ipynb - Colaboratory.pdf → docs/hugging-face.ipynb - Colaboratory.pdf
diff --git a/docs/index.md b/docs/index.md
@@ -1,2 +1,16 @@
-# Quick Test
-What is the default MKDocs homepage...
+---
+title: Howdy There!
+---
+
+This website hosts my work from my ML experience at UTD. I learned to create primarily predictive models on structured data utilizing R and Python to implement linear regression to deep learning.
+
+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.
+
+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.
+
+Feel free to explore my projects and reach out if you have any questions or opportunities that align with my interests.
+## Highlights
+
+Out of my different projects, I'm most proud of the work I did researching [[Summary_of_Attention_Article.pdf|explainability in attention based models]] and fine tuning Google's MobileNetV2 for [[keras_image_recognition.pdf|identifying grains of rice]].
+
+![[Pasted image 20231029141843.png]]
diff --git a/docs/ML Work/keras_image_recognition.pdf → docs/keras_image_recognition.pdf b/docs/ML Work/keras_image_recognition.pdf → docs/keras_image_recognition.pdf
diff --git a/docs/ML Work/linear classification.pdf → docs/linear classification.pdf b/docs/ML Work/linear classification.pdf → docs/linear classification.pdf
diff --git a/docs/ML Work/linear regression.pdf → docs/linear regression.pdf b/docs/ML Work/linear regression.pdf → docs/linear regression.pdf
diff --git a/docs/ML Work/ml-overview.pdf → docs/ml-overview.pdf b/docs/ML Work/ml-overview.pdf → docs/ml-overview.pdf
diff --git a/docs/NLP Work/ngrams-assignment.pdf → docs/ngrams-assignment.pdf b/docs/NLP Work/ngrams-assignment.pdf → docs/ngrams-assignment.pdf
diff --git a/docs/obsidian/copart internship.md b/docs/obsidian/copart internship.md
diff --git a/docs/obsidian/portfolio cleanup.md b/docs/obsidian/portfolio cleanup.md
diff --git a/docs/NLP Work/overview-of-nlp.pdf → docs/overview-of-nlp.pdf b/docs/NLP Work/overview-of-nlp.pdf → docs/overview-of-nlp.pdf
diff --git a/docs/NLP Work/report.pdf → docs/report.pdf b/docs/NLP Work/report.pdf → docs/report.pdf
diff --git a/docs/NLP Work/sentence_parsing.pdf → docs/sentence_parsing.pdf b/docs/NLP Work/sentence_parsing.pdf → docs/sentence_parsing.pdf
diff --git a/docs/ML Work/similarities classification.pdf → docs/similarities classification.pdf b/docs/ML Work/similarities classification.pdf → docs/similarities classification.pdf
diff --git a/docs/ML Work/similarities main.pdf → docs/similarities main.pdf b/docs/ML Work/similarities main.pdf → docs/similarities main.pdf
diff --git a/docs/ML Work/similarities regression.pdf → docs/similarities regression.pdf b/docs/ML Work/similarities regression.pdf → docs/similarities regression.pdf
diff --git a/docs/NLP Work/summary.pdf → docs/summary.pdf b/docs/NLP Work/summary.pdf → docs/summary.pdf
diff --git a/docs/NLP Work/text-classification.pdf → docs/text-classification.pdf b/docs/NLP Work/text-classification.pdf → docs/text-classification.pdf
diff --git a/docs/NLP Work/wordnet.pdf → docs/wordnet.pdf b/docs/NLP Work/wordnet.pdf → docs/wordnet.pdf
diff --git a/mkdocs.yml b/mkdocs.yml
@@ -1,11 +1,9 @@
-site_name: ZaiquiriW
+site_name: Zaiquiri Canoot
 site_description: All things ZaiquiriW
 site_url: https://zaiquiri.github.io
 
 theme:
     name: material
-    logo: assets/meta/favicons.png
-    favicon: assets/meta/favicons.png
     custom_dir: overrides
     font:
         text: Ubuntu
@@ -16,19 +14,19 @@ theme:
     # Light mode
     - media: "(prefers-color-scheme: light)"
       scheme: default
-      primary: teal
-      accent: light blue
+      primary: yellow
+      accent: purple
       toggle:
-        icon: material/toggle-switch-off-outline
+        icon: material/weather-sunny
         name: Switch to dark mode
 
     # Dark mode
     - media: "(prefers-color-scheme: dark)"
       scheme: slate
-      primary: blue
-      accent: indigo
+      primary: deep-purple
+      accent: yellow
       toggle:
-        icon: material/toggle-switch
+        icon: material/weather-night
         name: Switch to light mode
     features:
         - navigation.indexes