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jdata

京东JData算法大赛-高潜用户购买意向预测入门程序(starter code)

jdata-1

a solution for 2017 JData competition,rank A: 139/4240，B: 97/4240

jdata-rank13

京东JData大数据比赛第13名的user模型

jieba

结巴中文分词

just-code

Just Code ! 针对面试训练算法题， 目前包括字节跳动面试题、 LeetCode 和剑指 offer ，持续扩容中 :star:

kaggle-ensemble-guide

Code for the Kaggle Ensembling Guide Article on MLWave

kaggle-solution

Solutions of Kaggle Competition

kaggle-titanic

kebi

基于crnn的中文印刷体识别

kkndme_tianya

天涯 kkndme 神贴聊房价

learn_dl

Deep learning algorithms source code for beginners

leetcode

LeetCode题解，151道题完整版

leetcode-1

:pencil2: LeetCode solutions in C++ 11

leetcode-2

LeetCode刷题记录与面试整理

leetcode-master

LeetCode 刷题攻略：配思维导图，各个类型的经典题目刷题顺序、经典算法模板，以及详细图解和视频题解。这里精选的题目都不是孤立的，而是由浅入深一脉相承的，相信只要按照刷题攻略上的顺序来学习，一定会有所收获！给个star支持一下吧！

leetcodetop

汇总各大互联网公司容易考察的高频leetcode题🔥

lets_ocr

A repository for OCR, which inlcudes some classical OCR algorithms Pytorch implementation such as CTPN, EAST and CRNN.

lianjia-scrawler

链家二手房租房在线数据，存量房交易服务平台数据，详细数据分析教程

libpku

贵校课程资料民间整理

lightgbm

A fast, distributed, high performance gradient boosting (GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. It is under the umbrella of the DMTK(http://github.com/microsoft/dmtk) project of Microsoft.

lihang-code

《统计学习方法》的代码实现

lstm

基于LSTM神经网络的时间序列预测

lstm-neural-network-for-time-series-prediction

LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data

machine-learning

:zap:机器学习实战（Python3）：kNN、决策树、贝叶斯、逻辑回归、SVM、线性回归、树回归

machine-learning-algorithms-implemented-by-python

《统计学习方法》--李航 书中算法实现

machine-learning-for-software-engineers

A complete daily plan for studying to become a machine learning engineer.

machine-learning-interview

算法工程师-机器学习面试题总结

machine-learning-with-python

此项目是我在学习《机器学习实战》这本书时的代码记录情况，用python实现，当然也会包括一些其他的机器学习算法，使用Python实现

machinelearning

Basic Machine Learning and Deep Learning

machinelearning-1

My blogs and code for machine learning. http://cnblogs.com/pinard