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    <title>Rodrigo Arenas — AI &amp; Machine Learning Blog</title>
    <link>https://www.rodrigo-arenas.com</link>
    <description>Artículos sobre IA, machine learning, MLOps y sistemas de datos por Rodrigo Arenas. Articles on AI, machine learning, MLOps, and data systems by Rodrigo Arenas.</description>
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    <item>
      <title><![CDATA[Extracción de Datos Estructurados desde Texto con LLMs]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/extraccion-datos-estructurados-llms</link>
      <guid>https://www.rodrigo-arenas.com/blogs/extraccion-datos-estructurados-llms</guid>
      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Extrae datos estructurados de texto con Python, Pydantic y LLMs: convierte facturas y ofertas de trabajo en objetos Python tipados y validados.]]></description>
      <category>LLMs &amp; Agents</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Structured Data Extraction from Text with LLMs]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/structured-data-extraction-with-llms</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/structured-data-extraction-with-llms</guid>
      <pubDate>Thu, 25 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Use Python, Pydantic, and LLMs to extract structured data from unstructured text. Turn invoices and job postings into typed, validated Python objects.]]></description>
      <category>LLMs &amp; Agents</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Agentes de IA con LangGraph para Análisis de Datos]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/agentes-ia-con-langgraph-analisis-datos</link>
      <guid>https://www.rodrigo-arenas.com/blogs/agentes-ia-con-langgraph-analisis-datos</guid>
      <pubDate>Thu, 18 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Construye un agente autónomo de análisis de datos con LangGraph: implementa el ciclo ReAct con herramientas y aprende cuándo usar agentes vs RAG.]]></description>
      <category>LLMs &amp; Agents</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[AI Agents with LangGraph for Data Analysis]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/ai-agents-with-langgraph-data-analysis</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/ai-agents-with-langgraph-data-analysis</guid>
      <pubDate>Thu, 18 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Build an autonomous data analysis agent with LangGraph: implement the ReAct loop with tools for querying data, and learn when to use agents vs RAG.]]></description>
      <category>LLMs &amp; Agents</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Orquesta Pipelines de ML con Prefect]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/orquesta-pipelines-ml-con-prefect</link>
      <guid>https://www.rodrigo-arenas.com/blogs/orquesta-pipelines-ml-con-prefect</guid>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Convierte scripts frágiles de entrenamiento en pipelines de ML robustos y observables con Prefect: reintentos, caché y re-entrenamiento programado.]]></description>
      <category>MLOps</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Orchestrate ML Pipelines with Prefect]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/orchestrate-ml-pipelines-with-prefect</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/orchestrate-ml-pipelines-with-prefect</guid>
      <pubDate>Thu, 11 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Go from fragile training scripts to robust, observable ML workflows using Prefect. Schedule retraining, handle failures gracefully, and monitor every run.]]></description>
      <category>MLOps</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Monitoreo de Modelos ML en Producción con Evidently]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/monitoreo-modelos-ml-produccion-evidently</link>
      <guid>https://www.rodrigo-arenas.com/blogs/monitoreo-modelos-ml-produccion-evidently</guid>
      <pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Detecta data drift y degradación de modelos ML en producción con Evidently AI: reportes automatizados y alertas antes de que tu modelo falle en silencio.]]></description>
      <category>MLOps</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[ML Model Monitoring in Production with Evidently]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/ml-model-monitoring-production-evidently</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/ml-model-monitoring-production-evidently</guid>
      <pubDate>Thu, 04 Jun 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn how to detect data drift and model degradation in production using Evidently AI. Build automated reports and alerts before your model silently fails.]]></description>
      <category>MLOps</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Tu Primer Modelo de Machine Learning con Scikit-learn]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/tu-primer-modelo-ml-sklearn</link>
      <guid>https://www.rodrigo-arenas.com/blogs/tu-primer-modelo-ml-sklearn</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Guía paso a paso para construir tu primer modelo de ML: exploración de datos, preprocesamiento, validación cruzada, ajuste de hiperparámetros y evaluación con scikit-learn.]]></description>
      <category>Aprendizaje automático</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Your First Machine Learning Model with Scikit-learn]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/your-first-ml-model-with-sklearn</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/your-first-ml-model-with-sklearn</guid>
      <pubDate>Thu, 21 May 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[A step-by-step guide to building your first ML model: data exploration, preprocessing, cross-validation, hyperparameter tuning, and evaluation — all with scikit-learn.]]></description>
      <category>Machine Learning</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Cómo Resolver Problemas de Scheduling con Python]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/como-resolver-problemas-de-scheduling-con-python</link>
      <guid>https://www.rodrigo-arenas.com/blogs/como-resolver-problemas-de-scheduling-con-python</guid>
      <pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Resuelve problemas de scheduling y rostering de empleados en Python con pyworkforce. Asigna trabajadores individuales a turnos respetando cobertura, reglas de descanso, turnos prohibidos y preferencias.]]></description>
      <category>Investigación de Operaciones</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[How to Solve Scheduling Problems in Python]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/how-to-solve-scheduling-problems-in-python</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/how-to-solve-scheduling-problems-in-python</guid>
      <pubDate>Thu, 14 May 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Solve employee scheduling and rostering problems in Python with pyworkforce. Assign individual workers to shifts while honoring coverage, rest rules, banned shifts, and preferences.]]></description>
      <category>Operations Research</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Métodos de Parámetros Adaptativos para Machine Learning]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/metodos-de-parametros-adaptativos-para-machine-learning</link>
      <guid>https://www.rodrigo-arenas.com/blogs/metodos-de-parametros-adaptativos-para-machine-learning</guid>
      <pubDate>Thu, 30 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Aprende cómo funcionan los parámetros adaptativos en sklearn-genetic-opt: usa ExponentialAdapter e InverseAdapter para ajustar mutación y cruzamiento.]]></description>
      <category>Machine Learning</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Adaptive Parameters Methods for Machine Learning]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/adaptive-parameters-methods-for-machine-learning</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/adaptive-parameters-methods-for-machine-learning</guid>
      <pubDate>Thu, 30 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn how adaptive parameter methods work in sklearn-genetic-opt: use ExponentialAdapter and InverseAdapter to adjust mutation and crossover on the fly.]]></description>
      <category>Machine Learning</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Selección Evolutiva de Características para Machine Learning]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/seleccion-evolutiva-de-caracteristicas-sklearn-genetic-opt</link>
      <guid>https://www.rodrigo-arenas.com/blogs/seleccion-evolutiva-de-caracteristicas-sklearn-genetic-opt</guid>
      <pubDate>Thu, 16 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Aplica selección evolutiva de características con GAFeatureSelectionCV de sklearn-genetic-opt y encuentra el subconjunto que maximiza el rendimiento del modelo.]]></description>
      <category>Machine Learning</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Evolutionary Feature Selection for Machine Learning]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/evolutionary-feature-selection-sklearn-genetic-opt</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/evolutionary-feature-selection-sklearn-genetic-opt</guid>
      <pubDate>Thu, 16 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Use evolutionary feature selection with GAFeatureSelectionCV from sklearn-genetic-opt to find the feature subset that maximizes your model's performance.]]></description>
      <category>Machine Learning</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Detección de Anomalías en Tiempo Real con Apache Kafka y Python]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/deteccion-de-anomalias-en-tiempo-real-apache-kafka-python</link>
      <guid>https://www.rodrigo-arenas.com/blogs/deteccion-de-anomalias-en-tiempo-real-apache-kafka-python</guid>
      <pubDate>Thu, 02 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Implementa un sistema de detección de anomalías en tiempo real usando Apache Kafka y Python. Aprende a procesar flujos de datos y detectar eventos inusuales al vuelo con confluent-kafka y scikit-learn.]]></description>
      <category>Sistemas de Datos</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Real-Time Anomaly Detection with Apache Kafka and Python]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/real-time-anomaly-detection-apache-kafka-python</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/real-time-anomaly-detection-apache-kafka-python</guid>
      <pubDate>Thu, 02 Apr 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Build a real-time anomaly detection system using Apache Kafka and Python. Learn to process streaming data and flag unusual events on the fly with confluent-kafka and scikit-learn.]]></description>
      <category>Data Systems</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Despliega un Modelo de Machine Learning con Sklearn, FastAPI y Docker]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/serve-modelo-machine-learning-sklearn-fastapi-docker</link>
      <guid>https://www.rodrigo-arenas.com/blogs/serve-modelo-machine-learning-sklearn-fastapi-docker</guid>
      <pubDate>Thu, 19 Mar 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Crea una API REST para desplegar modelos de scikit-learn con FastAPI y Docker: del entrenamiento a un contenedor listo para producción en minutos.]]></description>
      <category>MLOps</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Deploy a Machine Learning Model Using Sklearn, FastAPI, and Docker]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/serve-machine-learning-model-sklearn-fastapi-docker</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/serve-machine-learning-model-sklearn-fastapi-docker</guid>
      <pubDate>Thu, 19 Mar 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn how to build a REST API to deploy scikit-learn models using FastAPI and Docker. From training to a production-ready containerized deployment in minutes.]]></description>
      <category>MLOps</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[¿Todavía Usas Grid Search para Optimización de Hiperparámetros?]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/todavia-usas-grid-search-para-hiperparametros</link>
      <guid>https://www.rodrigo-arenas.com/blogs/todavia-usas-grid-search-para-hiperparametros</guid>
      <pubDate>Thu, 05 Mar 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Compara grid search, random search y algoritmos evolutivos para ajustar hiperparámetros, y descubre cuándo GASearchCV de sklearn-genetic-opt gana.]]></description>
      <category>Machine Learning</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Are You Still Using Grid Search for Hyperparameters Optimization?]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/are-you-still-using-grid-search-for-hyperparameters</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/are-you-still-using-grid-search-for-hyperparameters</guid>
      <pubDate>Thu, 05 Mar 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Compare grid search, random search and evolutionary algorithms for hyperparameter tuning, and see when GASearchCV from sklearn-genetic-opt wins.]]></description>
      <category>Machine Learning</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Ajusta Tu Modelo de Scikit-learn Usando Algoritmos Evolutivos]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/ajusta-tu-modelo-sklearn-con-algoritmos-evolutivos</link>
      <guid>https://www.rodrigo-arenas.com/blogs/ajusta-tu-modelo-sklearn-con-algoritmos-evolutivos</guid>
      <pubDate>Thu, 19 Feb 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Aprende a optimizar hiperparámetros de scikit-learn con algoritmos genéticos: GASearchCV, espacios tipados, adaptadores y callbacks de early stopping.]]></description>
      <category>Machine Learning</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Tune Your Scikit-learn Model Using Evolutionary Algorithms]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/tune-sklearn-model-evolutionary-algorithms</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/tune-sklearn-model-evolutionary-algorithms</guid>
      <pubDate>Thu, 19 Feb 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn to tune scikit-learn hyperparameters with genetic algorithms: GASearchCV setup, typed search spaces, adapters and early-stopping callbacks.]]></description>
      <category>Machine Learning</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Gestiona el Ciclo de Vida de Machine Learning con MLflow en Python]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/gestiona-ciclo-de-vida-ml-con-mlflow</link>
      <guid>https://www.rodrigo-arenas.com/blogs/gestiona-ciclo-de-vida-ml-con-mlflow</guid>
      <pubDate>Thu, 05 Feb 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Aprende a usar MLflow en Python para rastrear experimentos, versionar modelos y gestionar el ciclo de vida de machine learning hasta el despliegue.]]></description>
      <category>MLOps</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Manage Your Machine Learning Lifecycle with MLflow in Python]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/manage-machine-learning-lifecycle-mlflow-python</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/manage-machine-learning-lifecycle-mlflow-python</guid>
      <pubDate>Thu, 05 Feb 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn how to use MLflow to track experiments, version models, and manage the complete machine learning lifecycle in Python, from training to deployment.]]></description>
      <category>MLOps</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Optimización de Planeación de Personal con Python]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/optimizacion-de-planeacion-de-personal-con-python</link>
      <guid>https://www.rodrigo-arenas.com/blogs/optimizacion-de-planeacion-de-personal-con-python</guid>
      <pubDate>Thu, 22 Jan 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Aprende a optimizar la planeación de personal en Python con pyworkforce. Calcula el headcount mínimo que cubre la demanda usando optimización con restricciones sobre Google OR-Tools.]]></description>
      <category>Investigación de Operaciones</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[Workforce Planning Optimization Using Python]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/workforce-planning-optimization-python</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/workforce-planning-optimization-python</guid>
      <pubDate>Thu, 22 Jan 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Learn how to optimize workforce staffing in Python with pyworkforce. Compute the minimum headcount that meets demand using constraint optimization on top of Google OR-Tools.]]></description>
      <category>Operations Research</category>
      <dc:language>en</dc:language>
    </item>
    <item>
      <title><![CDATA[Cómo construir un sistema RAG con LangChain y Python]]></title>
      <link>https://www.rodrigo-arenas.com/blogs/introduccion-a-rag-con-langchain</link>
      <guid>https://www.rodrigo-arenas.com/blogs/introduccion-a-rag-con-langchain</guid>
      <pubDate>Thu, 08 Jan 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Construye un sistema RAG con LangChain y Python: estrategias de chunking, recuperación con MMR, evaluación con RAGAS y errores comunes en producción.]]></description>
      <category>LLMs &amp; RAG</category>
      <dc:language>es-co</dc:language>
    </item>
    <item>
      <title><![CDATA[How to Build a RAG System with LangChain and Python]]></title>
      <link>https://www.rodrigo-arenas.com/en/blogs/introduction-to-rag-with-langchain</link>
      <guid>https://www.rodrigo-arenas.com/en/blogs/introduction-to-rag-with-langchain</guid>
      <pubDate>Thu, 08 Jan 2026 00:00:00 GMT</pubDate>
      <description><![CDATA[Build a RAG system with LangChain and Python: chunking strategies, MMR retrieval, RAGAS evaluation, and the failure modes that break RAG in production.]]></description>
      <category>LLMs &amp; RAG</category>
      <dc:language>en</dc:language>
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