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on a mission
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ricardobrein/README.md

Hi there, I'm Ricardo. 👋

I'm following a self-taught path to build things in mobile development with Flutter and everything related to AI.

When i started to learn programming I truly knew what I wanted to dedicate myself to. Allowing me to explore different fields of knowledge and discover something new every day, thats why i decided to learn in a self-taught way. So, i would like to understand all the procces of how the modern software and applications are created.

I'm just an enthusiast who manipulate and try to get the most of the tools created by remarkable individuals and big tech companies I aspire to be/work with them!

Untill now, I never stop learning through self-study (books, online corses, Yt) and various professional certifications. Where I'm learn Python, Dart, Flutter, Data analytics, Statistics, Machine learning models, Big Data Architecture, MLOps and business intelligence.

What really appeals to me, is to be involved in the entire data lifecycle, including processes like ETL, training, testing, and deploying models. I find it fascinating because it allows me to be involved in various aspects, from gathering data to extract knowledge from them and developing models that can be utilized with a purpose

I like to believe that I am part of something that has changing the world for better.

Currently loving, reading & learning📚

  • Everything about app development with Flutter and Dart
  • More about backend, deploy ML models and data pipelines
  • Docker containers and kubernetes
  • Mlops

💬 I like discussing various topics related to the the latest trends on AI, programming, and its implications in philosophy, economics, geopolitics, psychology, and sociology.

⚠️ I'm not a frequently user of social media but reach me out at:

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  1. Customer-churn-prediction-models Customer-churn-prediction-models Public

    Análisis de los casos de abandono e implementación de algunos modelos de ML para predecir la rotación clientes

    Jupyter Notebook

  2. prediction-churn-streamlit-app prediction-churn-streamlit-app Public

    Despliegue de un modelo de Random forest en streamlit para predecir los clientes que son propensos a abandonar la compañia.

    Python

  3. Customer-clustering-segmentation-for-marketing-department Customer-clustering-segmentation-for-marketing-department Public

    Clustering con K-means de los clientes de una entidad bancaria, para apoyar las decisiones del departamento de marketing

    Jupyter Notebook