By now I'm actively learning about Data Science Topics and I think the better way to learn is practicing. In this order, I have this repository where I made short projects in order to show and practice what i've learned.
- Data_visualization: A calendar plot about USDPEN prices.
- FeatureEncoding Challenge: Kaggle competition about encoding techniques.
- Finance_with_Python: Markowitz Optimization Notebook and a Little Backtest for Forwards and Options Portfolio.
- Peru Exports Model: A Ml-forecast approach for Peruvian non-traditional exports.
- Pytorch Training: Notebooks about Pytorch topics and features.
- Retail Churn Model: A churn-case with real encrypted data for a well know company.
- Retail Sales Model: Sales prediction for a internal Kaggle competition of SaturdaysAI-Lima
- Topic Modelling: LDA methods for Alicorp Financial statements (run on local)
- MLFlow Training: A Simple Deployment with MLFlow Models & Packaging.