Added links to the class_projects page

class_projects.md

@@ -30,6 +30,7 @@ key: page-home
         <li> Created a CNN Model with 7 fully connected layers. Trained it on a labelled art-artist dataset</li>
         <li> Got a 13% higher accuracy when testing against shallow ML techniques for 25 artists</li>
       </ul>
+      <h3 markdown="1" align="center">[Click for more details](https://github.com/sagars2/CMU_24787_Final_Project/blob/main/AIML_Final_Project/art_classifiation_report.pdf)</h3>
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@@ -56,14 +57,15 @@ key: page-home
         <li> Visualized these paths using RViz in a custom search map, given planning parameters such as curvature radius, start and goal pose </li>
         <li> Goal: Achieving Goal State with maximum reduction in Shannon Entropy without coverage of the same area</li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <h3 markdown="1" align="center">[Click for more details](https://docs.google.com/presentation/d/1-fihgc-8xvEf03UOxG9EC_AOIo7JM6kM/edit?usp=sharing&ouid=111440446402993602690&rtpof=true&sd=true)</h3>
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 <!-- <h1 align="center">Undergraduate Research</h1> -->
 
 ## Localization and Mapping | Carnegie Mellon University
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@@ -72,16 +74,17 @@ key: page-home
           <img class="image" src="/assets/images/class_projects/localization_and_mapping.png"/>
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-        <h3>Graph Optimization of ORB Features</h3>
+    <h3>Graph Optimization of ORB Features</h3>
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       <ul style="font-size:16px">
-      <li> Extracted ORB features and implemented Graph Factorization using GTSAM in Python3 and compared this against ground truth measurements</li>
-      <li>Used the GTSAM functions and visual odometry to match points between frames</li>
+        <li>Extracted ORB features and implemented Graph Factorization using GTSAM in Python3 and compared this against ground truth measurements</li>
+        <li>Used the GTSAM functions and visual odometry to match points between frames</li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <!-- <h3 markdown="1" align="center">[Click for more details](http://www.google.com)</h3> -->
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@@ -105,7 +108,7 @@ key: page-home
         <li>Did spatial pyramid matching for scene classification</li>
         <li>Trained a CNN to be able to read handwritten text</li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <h3 markdown="1" align="center">[Click for more details](https://github.com/sagars2/CMU_16720_CV)</h3>
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@@ -131,7 +134,7 @@ key: page-home
         <li>Computed manufacturing costs using aPriori software which takes a CAD model as an input</li>
         <li>Re-ideation resulted in a 7% decrease in manufacturing costs</li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <h3 markdown="1" align="center">[Click for more details](https://sagars24.wixsite.com/mysite)</h3>
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@@ -154,7 +157,7 @@ key: page-home
         <li>Constructed a miniature stirling engine using a tea-light candle to demonstrate the Stirling cycle principles</li>
         <li>Objective was to lift a quarter through the Stirling Cycle </li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <h3 markdown="1" align="center">[Click for more details](https://vidushp2.wixsite.com/me-200-22/prototyping)</h3>
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@@ -177,7 +180,7 @@ key: page-home
         <li>Tuned PID balance control using MATLAB and Simulink, accomplishing optimal balance by adjusting system stability and response through state-space pole placement tuning </li>
         <li>Upgraded Segbot functionality by integrating ultrasonic sensor hardware and software in C, enabling obstacle detection</li>
       </ul>
-      <h3 align="center"> Click for more details </h3>
+      <h3 markdown="1" align="center">[Click for more details](https://www.hackster.io/sagars2/uiuc-me461-self-balancing-segbot-with-obstacle-detection-013051)</h3>
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