Python model to estimate the probability of credit card usage (Jupiter Notebook)

Create a model to estimate the probability of use the credit card, using max 50 variables.

It must be done using: Random Forest, Logistic Regression.

Sample database "[login to view URL]" with 7700 records and 397 variables.

The basis train can be: train 80% and test 20%

Target variable: FLG_ACTIVACION_0_12 (1 = used the card, 0 = not used).


- Just Jupiter notebook file with comments and commands.

PD. I attach an example for xgBoost (jupiter notebook as example).

Skills: Python, Machine Learning (ML), Data Analytics, Statistics, Data Science

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Hello sir ! I have an Engineer degree in Applied mathematical modelling , Economics, , Statistics with 9 years of professional experience working as a Quantitative Analyst (in the field of Statistics). . I can start More

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I'm well versed with machine learning, in a previous project I completed a similar project with XGBoost Feel free to ping me if my profile interests you.

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Hi I am a mathematician. I have a strong knowledge in predicting results using numpy and sklearn frameworks.I have done a previous review with jupyter notebook where I had to ranking the performance of NBA players usin More

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