Este es el tercer y �ltimo volumen de la serie Ciencia de Datos Desde Cero. Tras aprender los fundamentos (Volumen 1) y dominar el an�lisis exploratorio y los primeros modelos predictivos (Volumen 2), aqu� te adentrar�s en el nivel profesional: modelos avanzados, an�lisis de Big Data y despliegue en producci�n.

En este libro aprender�s a:

Entrenar y optimizar modelos de Machine Learning avanzados: �rboles de Decisi�n, Random Forest, Gradient Boosting.
Explicar predicciones con SHAP e interpretar la importancia de variables.
Analizar datos masivos con PySpark, comparando su potencia frente a Pandas.
Guardar y desplegar modelos con Flask y ponerlos en la nube (Heroku / AWS).
Implementar pr�cticas de MLOps: versionado de datos, pipelines automatizados y control de modelos.
Integrar todo en un proyecto real de predicci�n de rotaci�n de empleados, desde el EDA hasta la presentaci�n final de resultados a negocio.

📌 Este volumen cierra la trilog�a y te lleva desde aprendiz hasta cient�fico de datos aut�nomo, capaz de afrontar proyectos completos en Machine Learning y Big Data.

Ideal para estudiantes, profesionales de datos, analistas de negocio y cualquier persona que quiera alcanzar un nivel avanzado en ciencia de datos con Python.

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