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Jesús Pérez Lorenzo 2025-01-27 19:10:39 +00:00
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@ -17,11 +17,12 @@ Based in [PrefSPEC: Performance Profiling-based Proactive Security Policy Enforc
# What is done so far ?
- [X] Good look and feel and interactions among processing, analisys and presentation
- [X] Using better software packages management
- [X] A notebook open lyke [Marimo](https://marimo.io/) to support alternative dataframes engines like [Polars](https://pola.rs/) rather than [Pandas](https://pandas.pydata.org/)
- [X] Use settings and structures to play with different settins and options
- [X] Implement a customize [LSTM](https://en.wikipedia.org/wiki/Long_short-term_memory) within notebooks
- [X] Good look and feel and interactions among processing, analisys and presentation layers
- [X] Using better software packages management like [uv](https://docs.astral.sh/uv/) to complement Python **pip**
- [X] A notebook open like [Marimo](https://marimo.io/) to support alternative dataframes engines like [Polars](https://pola.rs/) rather than [Pandas](https://pandas.pydata.org/)
- [X] Use settings and structures to play with different settinigs and options
- [X] Implement a customize one [LSTM](https://en.wikipedia.org/wiki/Long_short-term_memory) model within notebooks
- [X] Use of different metrics to apply to the training models with custumezable adjustments
- [X] Use notebooks as python scripts for command-line use cases like collect predictions or automatic train models
- [X] Use [Dry](https://en.wikipedia.org/wiki/Don%27t_repeat_yourself) to reuse code and centralize common tasks like settings or loading resources. This is main use and existence of [lib_perfspec.py](learning/python/lib_perfspec.py)
- [X] Spliting basic tasks among seveal specific **notebooks**: