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acl_defect_prediction

An approach to defect prediction on unlabeled datasets

aeeem-and-other-sdp-datasets

ailearning

AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP

at4chinesener

Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism

autoticket

大麦网自动抢票工具

awesome-seml

A curated list of articles that cover the software engineering best practices for building machine learning applications.

bert-as-service

Mapping a variable-length sentence to a fixed-length vector using BERT model

class-overlap

This is class overlap for SDP

code2vec

TensorFlow code for the neural network presented in the paper: "code2vec: Learning Distributed Representations of Code"

codesensor

ANTLR 3 fuzzy parser

coursera-ml-andrewng-notes

吴恩达老师的机器学习课程个人笔记

cs-notes

:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++

dataminingalgorithm

数据挖掘18大算法实现以及其他相关经典DM算法

defectdata

An R package of Defect Prediction Datasets for Software Engineering Research

deye

Keep an Eye on Defects Inspection.

dgcnn

fault-prediction-using-nasa-mdp-dataset

Identifying the best algorithm for defect prediction in softwares and providing the most accurate results. The Metrics Data Program dataset provided by NASA has been used.

featureselectionsandextractions

feature selections and extractions

gan

Resources and Implementations of Generative Adversarial Nets: GAN, DCGAN, WGAN, CGAN, InfoGAN

god-of-bigdata

专注大数据学习面试，大数据成神之路开启。Flink/Spark/Hadoop/Hbase/Hive...

javalang

Pure Python Java parser and tools

keras-attention

这个仓库主要包含了LSTM、卷积神经网络中，注意力机制的实现。

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-experiments

🤖 Interactive Machine Learning experiments: 🏋️models training + 🎨models demo

machine-learning-learning-notes

周志华《机器学习》又称西瓜书是一本较为全面的书籍，书中详细介绍了机器学习领域不同类型的算法(例如：监督学习、无监督学习、半监督学习、强化学习、集成降维、特征选择等)，记录了本人在学习过程中的理解思路与扩展知识点，希望对新人阅读西瓜书有所帮助！

machine_learning_derivation

notes of machine learning algorithm derivation

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。

ml_for_learner

Implementations of the machine learning algorithm with Python and numpy

nasadefectdataset

NASA Cleaned Defect Datasets

nlp_tutorial

NLP入门指南