Update README.md

README.md

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-# Ml-models
+# Ml-models
+
+## first-model : 
+  We trained the artificial_neural_network_images model and the support vector machine on traffic sign classification dataset
+
+  #### dataset details : 
+  This data set contains 6358 manually labeled category labels. The labels include the following 10 categories: “GuideSign”, “M1”, “M4, “M5”, “M6”, “M7”, “P1”, “P10_50”, “P12”, “W1”, corresponding to ten Different traffic sign categories. All data has been manually divided into training set and test set according to the proportion, and the relevant training set annotation json file is provided.
+  The data set contains two folders train and test, as well as a unified train.json file to save the annotations of all training data sets. The image tags save the dictionary serialized in json format, and all the annotations are saved in train.json Under the key named annotations in the file.
+
+  You can download and get more details for dataset through the link :
+
+   https://www.kaggle.com/datasets/wjybuqi/traffic-sign-classification-and-recognition
+
+   # Results
+<table>
+<thead>
+  <tr>
+    <th>Operation Mode</th>
+    <th colspan="1">accuracy</th>
+    <th colspan="1">loss</th>
+  </tr>
+</thead>
+<tbody>
+  <tr>
+  </tr>
+  <tr>
+    <td>Ann</td>
+    <td>88.44%</td>
+    <td>40.25%</td>
+  </tr>
+  <tr>
+  </tr>
+  <tr>
+</tbody>
+</table>
+
+<br/>
+
+### second-model : 
+  We trained the artificial_neural_network_images model and the support vector machine on Students Performance in Exams dataset
+
+  You can download and get more details for dataset through the link :
+
+   https://www.kaggle.com/datasets/spscientist/students-performance-in-exams
+
+   # Results
+<table>
+<thead>
+  <tr>
+    <th>Operation Mode</th>
+    <th colspan="1">accuracy</th>
+    <th colspan="1">loss</th>
+  </tr>
+</thead>
+<tbody>
+  <tr>
+  </tr>
+  <tr>
+    <td>Ann</td>
+    <td>89.38%</td>
+    <td>23.21%</td>
+  </tr>
+  <tr>
+  </tr>
+  <tr>
+</tbody>
+</table>
+
+
+