sauvegarder le modèle

app.py

@@ -0,0 +1,17 @@
+import pickle  # Pour sauvegarder et charger le modèle
+from sklearn.feature_extraction.text import CountVectorizer  # Transformer le texte en nombres
+
+
+# Charger le modèle sauvegardé
+with open('sms_spam_detector_model.pkl','rb') as file: 
+    model=pickle.load(file)
+    
+# Fonction pour prédire si un message est du spam ou non
+def predict_spam(message):
+    # Convertir les messages en nombres
+    vectorizer = CountVectorizer()
+    message_transformed = vectorizer.transform([message])
+    prediction = model.predict(message_transformed)
+    return "SPAM ❌" if prediction[0] == 1 else "HAM ✅"
+
+

sms_spam_detector_model.pkl

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:be5baf4afe665e8089958c71f193dc574c19c79595cdbb689adc302586364cac
+size 279432

spam-detector-Mathis-AI.ipynb

@@ -18,7 +18,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 12,
    "id": "8a313f24",
    "metadata": {},
    "outputs": [],
@@ -27,6 +27,7 @@
     "import numpy as np  # Calculs mathématiques\n",
     "import matplotlib.pyplot as plt  # Affichage de graphiques\n",
     "import seaborn as sns  # Visualisation de données\n",
+    "import pickle  # Sauvegarder et charger des modèles\n",
     "from sklearn.feature_extraction.text import CountVectorizer  # Transformer le texte en nombres\n",
     "from sklearn.model_selection import train_test_split  # Séparer les données\n",
     "from sklearn.naive_bayes import MultinomialNB  # Modèle d'apprentissage\n",
@@ -393,7 +394,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 11,
    "id": "8f4f505b",
    "metadata": {},
    "outputs": [
@@ -403,7 +404,7 @@
        "<Axes: xlabel='label', ylabel='count'>"
       ]
      },
-     "execution_count": 14,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -422,13 +423,38 @@
     "sns.countplot(x='label', data=df)"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "55444fb4",
+   "metadata": {},
+   "source": [
+    "### Sauvegarder le model "
+   ]
+  },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 13,
    "id": "dba57e87",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "\n",
+    "# Sauvegarder le modèle \n",
+    "\n",
+    "with open('sms_spam_detector_model.pkl','wb') as file:\n",
+    "    pickle.dump(model,file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "6ebccf7a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('dht11_model.pkl','rb') as file: \n",
+    "    model=pickle.load(file)"
+   ]
   }
  ],
  "metadata": {