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📓 [Active] Portafolio of data science projects. Using: Python, PyTorch, Spark, Tensorflow, Scikit, Keras. Includes Classification, Regression, Time series, NLP, Deep learning, among others.

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Data Science Portafolio

OverviewHow To UseDescriptionCreditsLicense

Project Status: Active – The project has reached a stable, usable state and is being actively developed.

Overview

Classification problems

  • Titanic's passenger prediction survivors rate

Project Folder | Jupyter Notebook | nbviewer

  • Reference: https://www.kaggle.com/c/titanic
  • Analysis of what sorts of people were likely to survive. Predicting which passengers survived the tragedy.
  • The best result I got was 0.80861. Reachable maximum accuracy is ~82-85%.

How to use

  • Requeriments

    • Docker
    • Docker-compose
  • Run

$ docker-compose up
  • Go to the notebook folder and throught jupyter access to the notebook (.ipynb). Description ====================== TBD

Credits

Gonzalo Javier Martinez Ramirez

Licence

Apache 2.0

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📓 [Active] Portafolio of data science projects. Using: Python, PyTorch, Spark, Tensorflow, Scikit, Keras. Includes Classification, Regression, Time series, NLP, Deep learning, among others.

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