A comprehensive toolkit and benchmark for tabular data learning, featuring 30 deep methods, more than 10 classical methods, and 300 diverse tabular datasets.

Tabular methods for reinforcement learning

Source for the sample efficient tabular RL submission to the 2019 NIPS workshop on Biological and Artificial RL

Implementations of various RL and Deep RL algorithms in TensorFlow, PyTorch and Keras.

ML models + benchmark for tabular data classification and regression

[ICML 2024] BiSHop: Bi-Directional Cellular Learning for Tabular Data with Generalized Sparse Modern Hopfield Model

tabular method cpp src

An investigation into tabular classification with deep NNs for ETHZ Machine Learning for Healthcare on the MIT-BIH arrythmia dataset .

Modular Names Classifier, Object Oriented PyTorch Model

Code examples for simple reinforcement learning projects

R.L. methods and techniques.

First task for my Reinforcement Learning class in Deusto. The research paper the main RL algorithms applied on the Frozen Lake env provided by GymOpenAI. Paper is avaible at:

The implementation of tabular solution methods in Reinformcement Learning, Sutton's book: Part I

In this we explore into a Question Answering task on structured relational data (Tables) and CSV data

This is a python script file that translates tree-graph information stored in a .txt file to complicated LaTeX code, which can be compiled into a pretty tree graph in LaTeX editor (ex. Overleaf).

Revisiting tabular and deep reinforcement learning methods.

Implementation of tabular methods for Reinforcement learning