niuwan1 Goto Github PK

deepctr

Easy-to-use,Modular and Extendible package of deep-learning based CTR models.

deepgbm

Implementation for the paper "DeepGBM: A Deep Learning Framework Distilled by GBDT for Online Prediction Tasks", which has been accepted by KDD'2019.

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

deeptables

DeepTables: Deep-learning Toolkit for Tabular data

defaultprobabilitypredictions

Predict probability of default based on SEC filings and general company data.

deltapy

DeltaPy - Tabular Data Augmentation

deviation-network

Source code of the KDD19 paper "Deep anomaly detection with deviation networks", weakly/partially supervised anomaly detection, few-shot anomaly detection

dgfraud

A Deep Graph-based Toolbox for Fraud Detection

distill-nn-tree

Distillation of Neural Network Into a Soft Decision Tree

dndt

Deep Neural Decision Trees

dtreeviz

A python library for decision tree visualization and model interpretation.

edit

EDiT: Interpreting Ensemble Models via Compact Soft Decision Trees (ICDM'19)

explicithighorderinteraction-keras

Explicit high order interaction models implemented in Keras, including: DCN, xDeepFM, AutoInt etc.

fast-autoaugment

Official Implementation of 'Fast AutoAugment' in PyTorch.

fast_retraining

Show how to perform fast retraining with LightGBM in different business cases

fico-explainable-ml-challenge-heloc-dataset

Course work of "STAT3612 Statistical Machine Learning" that uses the same dataset HELOC as the FICO Explainable Machine Learning Challenge.

fico-xml-challenge

Submission for the FICO Explainable Machine Learning Challenge

financial-machine-learning

A curated list of practical financial machine learning (FinML) tools and applications in Python.

fully-differentiable-deep-ndf-tf

Fully differentiable deep-neural decision forest in tensorflow

gaminet

Generalized additive model with pairwise interactions

gc

generative-causal-explanations

Code for "Generative causal explanations of black-box classifiers"

gesture-recognition

graphenhancedmachinelearningforfraud

This project is part of a master's thesis studying how supervised learning models for detecting fraud can be improved by incorporating features based on graph theory

han

Heterogeneous Graph Neural Network

hierarchical-elm-network

IJCNN 2015 Hierarchical extreme learning machine for unsupervised representation learning

hyperspectral-image-super-resolution-benchmark

A list of hyperspectral image super-solution resources collected by Junjun Jiang

image-quality-assessment-benchmark

A collection of state-of-the-art image quality assessment algorithms

imbalance-xgboost

XGBoost for label-imbalanced data: XGBoost with weighted and focal loss functions

imbalanced-algorithms

Python-based implementations of algorithms for learning on imbalanced data.