This is your work, valued
ML_Notes. 机器学习算法的公式推导以及numpy实现
2.1kGNN_Notes. 图神经网络(GNN)学习笔记
81ML_imblearn. 类别不平衡学习,包括采样、代价敏感学习、决策输出补偿以及集成学习等内容
38Stacking_Ensembles. Stacking classification and regression
25EasyMLOps. EasyMLOps is an efficient Machine Learning Operations framework that builds modeling tasks through Pipeline approach. It supports model training, prediction, testing, feature storage, monitoring and more. Simply wrap with Flask or FastApi to deploy to production.
21Text_Representation. 基于gensim对BOW,TFIDF,LDA,LSI,W2V等传统的文本表示模型进行简单的封装,并添加了chi2,互信息等特征选择方法
12gbdt-is-all-you-need. 收集、整理其他技术与gbdt的融合,期望既能保留其他技术所带来的效果提升,又能保留gbdt模型的良好可解释性
4pipenlp. 以Pipeline的方式构建NLP任务,包括文本清洗、关键词提取、特征抽取、文本分类等任务
4Graphx_Notes. Graphx学习笔记
4faster-lgbm-predictor. 加速lgbm的预测速度
1zhulei227. Config files for my GitHub profile.
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