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Daudsarfraz · Jul 2, 2024 · d4db2d1 · d4db2d1
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Showing 2 changed files with 16 additions and 3 deletions.
diff --git a/index.html b/index.html
@@ -732,6 +732,18 @@ <h4>Russian Language Sentiment Analysis</h4>
           </div>
         </div>
 
+        <div class="col-lg-4 col-md-6 portfolio-item filter-project-ds">
+          <center><h4>Pakistan Food Prices Analysis</h4></center>
+          <div class="portfolio-wrap">
+            <img src="assets/img/project/food_prices.png" class="img-fluid" alt="" height="2500" width="12000">
+            <div class="portfolio-info">
+              <h4>Pakistan Food Prices Analysis</h4>
+              <div class="portfolio-links">
+                <a href="projects/pakistan_food_price.html" data-gall="portfolioDetailsGallery" data-vbtype="iframe" class="venobox" title="Project Details"><i class="bx bx-info-circle"></i></a>
+              </div>
+            </div>
+          </div>
+        </div>
         <div class="col-lg-4 col-md-6 portfolio-item filter-project-ml">
           <center><h4>MNIST Digit recognization</h4></center>
           <div class="portfolio-wrap">

diff --git a/projects/pakistan_food_price.html b/projects/pakistan_food_price.html
@@ -43,11 +43,12 @@
 
           <div class="col-lg-12 portfolio-info">
             <br>
-            <h2 style="color:#12d640">Sentiment Analysis</h2>
+            <h2 style="color:#12d640">Pakistan Food Price Analysis</h2>
 
             <ul>
-              <li><strong>Tech Stack</strong>: Python (version 3.7+), Pandas, NumPy, Scikit-learn, SVM, KNN, DT, XGBoost, Random Forest, Logistic Regression  </li>
-              <li><strong>Github URL</strong>: <a href="https://github.com/Daudsarfraz/twitter_sentiment_analysis/tree/main" target="_blank">Project Link</a></li>
+              <li><strong>Tech Stack</strong>: Python (version 3.7+), numpy, pandas, matplotlib, plotly, seaborn, sklearn -> linear_model, svm, MLPRegressor,  sklearn.ensemble -> RandomForestRegressor, AdaBoostRegressor, sklearn.tree -> DecisionTreeRegressor, sklearn.metrics -> mean_squared_error, mean_absolute_error,  r2_score, explained_variance_score, sklearn.model_selection -> train_test_split
+                preprocessing -> LabelEncod  </li>
+              <li><strong>Github URL</strong>: <a href="https://github.com/Daudsarfraz/Pakistan-Food-Price-Analysis" target="_blank">Project Link</a></li>
             </ul>
 
             <p>