diff --git a/CHANGELOG.md b/CHANGELOG.md
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+# Changelog
+
+## [1.0.0] - 2023-10-27
+### Added
+- Nueva rama `feature/salary-prediction`.
+- Endpoint de API `/api/predict` que devuelve JSON.
+- Archivo de pruebas `test_app.py`.
+
+### Changed
+- Se actualizó la interfaz de usuario para mejorar la experiencia.
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diff --git a/README1.md b/README1.md
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+# Predicción de Salarios - ML Flask App
+
+## Descripción
+Esta aplicación utiliza un modelo de Machine Learning para predecir el salario de un empleado basado en sus años de experiencia y habilidades.
+
+## Instalación
+1. Clonar el repo.
+2. Crear entorno virtual: `python -m venv venv`.
+3. Instalar dependencias: `pip install -r requirements.txt`.
+
+## Cómo usar
+Ejecuta `python app.py` y abre `http://localhost:5000` en tu navegador.
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diff --git a/application.py b/application.py
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--- a/application.py
+++ b/application.py
@@ -2,6 +2,14 @@
 from flask import Flask, request, jsonify, render_template
 import pickle
 
+#########################################################
+import sys
+import sklearn.linear_model._base as s_base
+sys.modules['sklearn.linear_model.base'] = s_base
+
+import pickle
+##########################################################
+
 application = Flask(__name__) #Initialize the flask App
 model = pickle.load(open('model.pkl', 'rb'))
 
diff --git a/test.py b/test.py
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+++ b/test.py
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+def test_home_status_code(client):
+    response = client.get('/')
+    assert response.status_code == 200
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