Create src/model.py

src/model.py

@@ -0,0 +1,15 @@
+from sklearn.ensemble import RandomForestClassifier
+
+model = RandomForestClassifier()
+
+def train_model(df):
+    """Train the AI model."""
+    df["target"] = (df["close"].pct_change() > 0.05).astype(int)  # Label: 1 if price increased by >5%
+    features = df[["close", "volume"]].dropna()
+    target = df["target"].dropna()
+    model.fit(features[:-1], target)
+
+def predict_growth(latest_data):
+    """Predict explosive growth."""
+    return model.predict([latest_data])
+