mglowacki100

pysystemtrade

Systematic Trading in python

Py-Boost

Python based GBDT implementation on GPU. Efficient multioutput (multiclass/multilabel/multitask) training

lppls

Library for fitting the LPPLS model to data.

tabular-benchmark

outrank

A Python library for efficient feature ranking and selection on sparse data sets.

C-GB

Condensed-Gradient Boosting

amorf

A Multi-Output Regression Framework in Python

NumeraiStarterPack

bio_corex

A flexible version of CorEx developed for bio-data challenges that handles missing data, continuous/discrete variables, multi-CPU, overlapping structure, and includes visualizations

hypertab

Code for "HyperTab: Hypernetwork Approach for Deep Learning on Small Tabular Datasets"

tabular-dl-tabr

The implementation of "TabR: Unlocking the Power of Retrieval-Augmented Tabular Deep Learning"

Concept_Drift_Handling

interpret

Fit interpretable models. Explain blackbox machine learning.

flash-attention

Fast and memory-efficient exact attention

ai-accelerators

signatory

Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)

expressive-resume

A beautiful resume/cover letter LaTeX template pair that are extraordinarily easy to use.

LightAutoML_GPU

facet

Human-explainable AI.

quantile-aggregation

Code for Flexible Model Aggregation for Quantile Regression

zr-obp

Open Bandit Pipeline: a python library for bandit algorithms and off-policy evaluation

EPIJudge

EPI Judge - Preview Release

slow-momentum-fast-reversion

This code accompanies the the paper Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection (https://arxiv.org/pdf/2105.13727.pdf).

humap

Hierarchical Uniform Manifold Approximation and Projection

redframes

General Purpose Data Manipulation Library

FETILDA

Source code and Data Repository for FETILDA: Fin-tuned Embeddings of Texts In Long Document Analysis

hopular

Hopular: Modern Hopfield Networks for Tabular Data

featurewiz

Use advanced feature engineering strategies and select best features from your data set with a single line of code. Created by Ram Seshadri. Collaborators welcome.

cog

Containers for machine learning

ML-Notebooks

:fire: Machine Learning Notebooks