A list of cool tools and libraries I like to keep around
Pandas profiling: Generates profile reports from a pandas DataFrame. The pandas df.describe() function is great but a little basic for serious exploratory data analysis. pandas_profiling extends the pandas DataFrame with df.profile_report() for quick data analysis.
SHAP: SHAP (SHapley Additive exPlanations) is a game theoretic approach to explain the output of any machine learning model. It connects optimal credit allocation with local explanations using the classic Shapley values from game theory and their related extensions (see papers for details and citations).
TPOT: Consider TPOT your Data Science Assistant. TPOT is a Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Pycaret: PyCaret is an open source, low-code machine learning library in Python that allows you to go from preparing your data to deploying your model within minutes in your choice of notebook environment.
Talos: Talos radically changes the ordinary Keras workflow by fully automating hyperparameter tuning and model evaluation. Talos exposes Keras functionality entirely and there is no new syntax or templates to learn.
A list of cool papers I'm definetely going to read some day
Meta-Gradient Reinforcement Learning: Gradient based
Population Based Training of Neural Networks: Evolutionary-based