mglowacki100

dirsearch

Web path scanner

lux

Automatically visualize your pandas dataframe via a single print! 📊 💡

river

🌊 Online machine learning in Python

lightly

A python library for self-supervised learning on images.

ngboost

Natural Gradient Boosting for Probabilistic Prediction

ppscore

Predictive Power Score (PPS) in Python

LightAutoML

LAMA - automatic model creation framework

graphtransformer

Graph Transformer Architecture. Source code for "A Generalization of Transformer Networks to Graphs", DLG-AAAI'21.

vega

AutoML tools chain

allRank

allRank is a framework for training learning-to-rank neural models based on PyTorch.

long-range-arena

Long Range Arena for Benchmarking Efficient Transformers

fast-soft-sort

Fast Differentiable Sorting and Ranking

GPBoost

Combining tree-boosting with Gaussian process and mixed effects models

PaCMAP

PaCMAP: Large-scale Dimension Reduction Technique Preserving Both Global and Local Structure

AutoML_Alex

State-of-the art Automated Machine Learning python library for Tabular Data

quantcon2018

xgboostExtension

xgboost Extension for Easy Ranking & TreeFeature

PRF

Probabilistic Random Forest: A machine learning algorithm for noisy datasets

AutoGBT

AutoGBT is used for AutoML in a lifelong machine learning setting to classify large volume high cardinality data streams under concept-drift. AutoGBT was developed by a joint team ('autodidact.ai') from Flytxt, Indian Institute of Technology Delhi and CSIR-CEERI as a part of NIPS 2018 AutoML for Lifelong Machine Learning Challenge.

KDDCUP_2020_AutoGraph_1st_Place

KDD CUP 2020 Automatic Graph Representation Learning: 1st Place Solution

sodeep

KTBoost

A Python package which implements several boosting algorithms with different combinations of base learners, optimization algorithms, and loss functions.

kaggle_mercedes

The 11th place solution of Mercedes-Benz Greener Manufacturing competition on Kaggle

TopoFilter

NeurIPS 2020, "A Topological Filter for Learning with Label Noise".

AutoGRD

AutoGRD is a meta-learning method for algorithm recommendation

numerai-experiments

Numerai Experiments

Factor-Modelling

drifting-features-analysis

continual-automl

Adaptations of AutoML libraries H2O, Autosklearn and GAMA for stream learning

ConFuse

CONFUSE: CONVOLUTIONAL TRANSFORM LEARNING BASED MULTI-CHANNEL FUSION FRAMEWORK