SISTEMA DE DETECCION DE ENLACES SPAM

Queremos implementar un sistema que sea capaz de detectar automáticamente si una página web contiene spam o no basándonos en su URL.

Paso 1: Carga del conjunto de datos

Paso 2: Preprocesamiento de enlaces Transformamos los datos para compatibilizarlos con el modelo que queremos entrenar. Segmentamos las URLs en partes según sus signos de puntuación, eliminamos las stopwords, lematiza, etcétera.

Paso 3: Construimos un SVM Implementamos un SVM con los parámetros por defecto. Lo entrenamos y analizamos sus resultados.

Paso 4: Optimizamos el modelo anterior Después de entrenar el SVM, optimizamos sus hiperparámetros utilizando un grid search o un random search.

Paso 5: Guardamos el modelo

ESTRUCTURA

The project is organized as follows:

• app.py - The main Python script that you run for your project.
• explore.py - A notebook to explore data, play around, visualize, clean, etc. Ideally the notebook code should be migrated to the app.py when moving to production.
• utils.py - This file contains utility code for operations like database connections.
• requirements.txt - This file contains the list of necessary python packages.
• models/ - This directory should contain your SQLAlchemy model classes.
• data/ - This directory contains the following subdirectories:
  • interin/ - For intermediate data that has been transformed.
  • processed/ - For the final data to be used for modeling.
  • raw/ - For raw data without any processing.

Setup

Prerequisites

Make sure you have Python 3.11+ installed on your. You will also need pip for installing the Python packages.

Installation

Clone the project repository to your local machine.

Navigate to the project directory and install the required Python packages:

pip install -r requirements.txt

Running the Application

To run the application, execute the app.py script from the root of the project directory:

python app.py

Contributors

This template was built as part of the 4Geeks Academy Data Science and Machine Learning Bootcamp by Alejandro Sanchez and many other contributors. Find out more about 4Geeks Academy's BootCamp programs here.

Other templates and resources like this can be found on the school GitHub page.