关于机器学习，深度学习，自然语言处理等各种算法的实现、示例，与博客文章配套，论文复现等.zip

# Magic-NLPer 主要是对应博客中使用到的代码 博客主页：[https://blog.csdn.net/u010366748](https://blog.csdn.net/u010366748) ## 目录 - [机器学习](#机器学习) - [深度学习](#深度学习) - [自然语言处理](#自然语言处理) - [论文阅读](#论文阅读) ## 机器学习 |博客地址 | 代码地址| ---|--- [线性回归（Linear Regression）原理小结](https://blog.csdn.net/u010366748/article/details/109545246)| [ML/LinearRegression线性回归/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/LinearRegression线性回归/t1.ipynb) [逻辑斯蒂回归（logistic regression）原理小结](https://blog.csdn.net/u010366748/article/details/109552858)| [ML/LogisticRegression逻辑斯蒂回归/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/LogisticRegression逻辑斯蒂回归/t1.ipynb) [最大熵（max entropy）模型原理小结](https://blog.csdn.net/u010366748/article/details/109628920)| 无 [决策树（Decision Tree）原理小结](https://blog.csdn.net/u010366748/article/details/109821147)| [ML/DecisionTree决策树/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/DecisionTree决策树/t1.ipynb) [随机森林（Random Forest）原理小结](https://blog.csdn.net/u010366748/article/details/110008640)| [ML/RandomForest随机森林/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/RandomForest随机森林/t1.ipynb) [梯度提升树（GBDT）原理小结](https://blog.csdn.net/u010366748/article/details/111060108)| [ML/GBDT梯度提升树/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/GBDT梯度提升树/t1.ipynb) [XGBoost使用](https://blog.csdn.net/u010366748/article/details/111083706)| [ML/XGBoostUsage/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/XGBoostUsage/t1.ipynb) [k近邻法（KNN）原理小结](https://blog.csdn.net/u010366748/article/details/112304969)| [ML/KNN/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/KNN/t1.ipynb) [感知机（Perception）原理小结](https://blog.csdn.net/u010366748/article/details/112740411)| [ML/Perception感知机/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/Perception感知机/t1.ipynb) [支持向量机（SVM）原理小结（1）线性支持向量机](https://blog.csdn.net/u010366748/article/details/112852999) <br>[支持向量机（SVM）原理小结（2）非线性支持向量机](https://blog.csdn.net/u010366748/article/details/113065986) <br>[支持向量机（SVM）原理小结（3）支持向量回归SVR](https://blog.csdn.net/u010366748/article/details/113066051)| [ML/SVM支持向量机/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/SVM支持向量机/t1.ipynb) [朴素贝叶斯（naive bayes）原理小结](https://blog.csdn.net/u010366748/article/details/113150864)| [ML/NaiveBayes朴素贝叶斯/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/NaiveBayes朴素贝叶斯/t1.ipynb) [EM（Expectation Maximization）算法原理小结](https://blog.csdn.net/u010366748/article/details/113446070)| 无 [隐马尔科夫模型（HMM）原理小结（1）](https://blog.csdn.net/u010366748/article/details/113554958) <br>[隐马尔科夫模型（HMM）原理小结（2）](https://blog.csdn.net/u010366748/article/details/113573732) <br>[手撸HMM实现词性标注（Part-of-speech）](https://blog.csdn.net/u010366748/article/details/113563529)| [ML/HMM隐马尔可夫模型/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/HMM隐马尔可夫模型/t1.ipynb) [条件随机场（CRF）原理小结（1）](https://blog.csdn.net/u010366748/article/details/113781150) <br>[条件随机场（CRF）原理小结（2）](https://blog.csdn.net/u010366748/article/details/113783526) <br>[BiLSTM-CRF实现中文命名实体识别（NER）](https://blog.csdn.net/u010366748/article/details/113784204)| [ML/CRF条件随机场/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/CRF条件随机场/t1.ipynb) [集成学习原理小结（AdaBoost & lightGBM demo）](https://blog.csdn.net/u010366748/article/details/113816465)| [ML/AdaBoost/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/AdaBoost/t1.ipynb) <br>[ML/AdaBoost/lightgbm_demo.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/MachineLearning/AdaBoost/lightgbm_demo.ipynb) [统计机器学习相关概念总结（上）](https://blog.csdn.net/u010366748/article/details/113829064) <br>[统计机器学习相关概念总结（中）](https://blog.csdn.net/u010366748/article/details/113829373) <br>[统计机器学习相关概念总结（下）](https://blog.csdn.net/u010366748/article/details/113829508)| 无 ## 深度学习 |博客地址 | 代码地址| ---|--- [transformer（上）论文解读+pytorch实现](https://blog.csdn.net/u010366748/article/details/111183674) <br>[transformer（下）机器翻译+pytorch实现](https://blog.csdn.net/u010366748/article/details/111269231)| [DL/Transformer/MachinTranslation/pytorch/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/DeepLearning/Transformer/MachinTranslation/pytorch/t1.ipynb) [条件随机场（CRF）原理小结（1）](https://blog.csdn.net/u010366748/article/details/113781150) <br>[条件随机场（CRF）原理小结（2）](https://blog.csdn.net/u010366748/article/details/113783526) <br>[BiLSTM-CRF实现中文命名实体识别（NER）](https://blog.csdn.net/u010366748/article/details/113784204)| [ML/CRF条件随机场/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/CRF条件随机场/t1.ipynb) ## 自然语言处理 |博客地址 | 代码地址| ---|--- [transformer（上）论文解读+pytorch实现](https://blog.csdn.net/u010366748/article/details/111183674) <br>[transformer（下）机器翻译+pytorch实现](https://blog.csdn.net/u010366748/article/details/111269231)| [NLP/MachineTranslation/transformer/pytorch/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/NLP/MachineTranslation/transformer/pytorch/t1.ipynb) [朴素贝叶斯（naive bayes）原理小结](https://blog.csdn.net/u010366748/article/details/113150864)| [NLP/Classification/binary/naive_bayes/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/tree/main/NLP/Classification/binary/naive_bayes/t1.ipynb) [隐马尔科夫模型（HMM）原理小结（1）](https://blog.csdn.net/u010366748/article/details/113554958) <br>[隐马尔科夫模型（HMM）原理小结（2）](https://blog.csdn.net/u010366748/article/details/113573732) <br>[手撸HMM实现词性标注（Part-of-speech）](https://blog.csdn.net/u010366748/article/details/113563529)| [ML/HMM隐马尔可夫模型/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/HMM隐马尔可夫模型/t1.ipynb) [条件随机场（CRF）原理小结（1）](https://blog.csdn.net/u010366748/article/details/113781150) <br>[条件随机场（CRF）原理小结（2）](https://blog.csdn.net/u010366748/article/details/113783526) <br>[BiLSTM-CRF实现中文命名实体识别（NER）](https://blog.csdn.net/u010366748/article/details/113784204)| [ML/CRF条件随机场/t1.ipynb](https://github.com/qingyujean/Magic-NLPer/blob/main/MachineLearning/CRF条件随机场/t1.ipynb) ## 论文阅读 |论文 | 发表年份| 博客地址 | ---|---|--- [Character-Level Language Modeling with Deeper Self-Attention](https://arxiv.org/abs/1808.04444) | AAAI 2019 | [论文笔记-Vanilla Transformer](https://blog.csdn.net/u010366748/article/details/114301942)| [Deep contextualized word representations](https://arxiv.org/abs/1802.05365) | NAACL 2018 | [ELMo论文笔记+源码分析](https://blog.csdn.net/u010366748/article/details/110309131)| [Attention Is All You Need](https://arxiv.org/abs/1706.03762) | NeurIPS 2017 | [transform