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100-days-of-ml-code

100-Days-Of-ML-Code中文版

adv-alstm

Code for paper "Enhancing Stock Movement Prediction with Adversarial Training" IJCAI 2019

adversarial

Code and hyperparameters for the paper "Generative Adversarial Networks"

algorithm_interview_notes-chinese

2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记

auto-sklearn

Automated Machine Learning with scikit-learn

autogrd

AutoGRD is a meta-learning method for algorithm recommendation

autoweka

Auto-WEKA

awesome-imbalanced-learning

A curated list of awesome imbalanced learning papers, codes, frameworks, and libraries. | 类别不平衡学习：论文、代码、框架与库

awesome-meta-learning

A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.

caret

caret (Classification And Regression Training) R package that contains misc functions for training and plotting classification and regression models

caret-1

compare Caret with DE

chatglm-6b

ChatGLM-6B: An Open Bilingual Dialogue Language Model | 开源双语对话语言模型

ckjm

Chidamber and Kemerer Java Metrics

ckjm-extended

An extended version of Tool for Calculating Chidamber and Kemerer Java Metrics (and many other metrics)

classimbalancelearning

This is the implementation code for the paper "Trainable Undersampling for Class-Imbalance Learning" published in AAAI2019

collaborativevae

costsensitiveclassification

CostSensitiveClassification Library in Python

crosspare

Cross-project defection prediction tooling

cumt-aipr-lab

d2l-en

Dive into Deep Learning: an interactive deep learning book with code, math, and discussions

d2l-pytorch

This project reproduces the book Dive Into Deep Learning (www.d2l.ai), adapting the code from MXNet into PyTorch.

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。英文版即伯克利“深度学习导论”教材。

deep-finance

Datasets, papers and books on AI & Finance.

deepinf

DeepInf: Social Influence Prediction with Deep Learning

deeplearning-500-questions

深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系[email protected] 版权所有，违权必究 Tan 2018.06

deepwalk

DeepWalk - Deep Learning for Graphs

diffnet

efficientnet-pytorch

A PyTorch implementation of EfficientNet

esem2016

Artefacts for ESEM2016 paper

explorekit