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dimensionality_reduction_alo_codes

特征提取/数据降维:PCA、LDA、MDS、LLE、TSNE等降维算法的python实现

east

A tensorflow implementation of EAST text detector

education

"数智教育"数据可视化创新大赛

elf

ELF: a platform for game research with AlphaGoZero/AlphaZero reimplementation

ema

Explanatory Model Analysis. Explore, Explain and Examine Predictive Models

entity-embedding-rossmann

espnet

End-to-End Speech Processing Toolkit

experiments_with_python

experiments with python

fairseq

Facebook AI Research Sequence-to-Sequence Toolkit written in Python.

fancyimpute

Multivariate imputation and matrix completion algorithms implemented in Python

feature-selector

Feature selector is a tool for dimensionality reduction of machine learning datasets

frcnn

Faster R-CNN / R-FCN :bulb: C++ version based on Caffe

huawei_code_share

https://www.datafountain.cn/competitions/334/details 赛题的baseline开源

iflytekmarketingalgorithm

2018科大讯飞AI营销算法大赛

interesting-python

有趣的Python爬虫和Python数据分析小项目(Some interesting Python crawlers and data analysis projects)

kaggle_competition_treasure

Describe past Kaggle solutions

kaldi

kdxf

科大讯飞 top2solution

kesci_ctrip

用户预订售卖房型概率预测--top1

leela-zero

Go engine with no human-provided knowledge, modeled after the AlphaGo Zero paper.

leeml-notes

李宏毅《机器学习》笔记，在线阅读地址：https://datawhalechina.github.io/leeml-notes

libpku

贵校课程资料民间整理

lightgbm

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

machine-learning

从零基础开始机器学习之旅

machine-learning-book

《机器学习宝典》包含：谷歌机器学习速成课程（招式）+机器学习术语表（口诀）+机器学习规则（心得）+机器学习中的常识性问题 （内功）。该资源适用于机器学习、深度学习研究人员和爱好者参考！

machine-learning_zhouzhihua

Exercises answers to the book "machine-learning" written by Prof. Zhou Zhihua of Nanjing University

mathmodel

研究生数学建模，本科生数学建模、数学建模竞赛优秀论文，数学建模算法，LaTeX论文模板，算法思维导图，参考书籍，Matlab软件教程，PPT

micronet

micronet, a model compression and deploy lib. compression: 1、quantization: quantization-aware-training(QAT), High-Bit(>2b)(DoReFa/Quantization and Training of Neural Networks for Efficient Integer-Arithmetic-Only Inference)、Low-Bit(≤2b)/Ternary and Binary(TWN/BNN/XNOR-Net); post-training-quantization(PTQ), 8-bit(tensorrt); 2、 pruning: normal、regular and group convolutional channel pruning; 3、 group convolution structure; 4、batch-normalization fuse for quantization. deploy: tensorrt, fp32/fp16/int8(ptq-calibration)、op-adapt(upsample)、dynamic_shape

mvi-evaluation

Missing value imputation and evaluation, especially for metabolomics data sets

ncov2019

query stats of infected coronavirus cases