未验证 提交 651581fa 编写于 作者: N NLP-LOVE 提交者: GitHub

完成 特征工程和优化方法模块

上级 82456eb2
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| 模块 | 章节 | 负责人(GitHub) | 联系QQ |
| -------- | ------------------------------------------------------------ | -------------------------------------- | --------- |
| 机器学习 | [1. 线性回归(Liner Regression)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/Liner%20Regression/1.Liner%20Regression.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [2. 逻辑回归(Logistics Regression)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/2.Logistics%20Regression/2.Logistics%20Regression.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [3. 决策树(Desision Tree)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.Desition%20Tree/Desition%20Tree.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [3.1 随机森林(Random Forest)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.1%20Random%20Forest/3.1%20Random%20Forest.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [3.2 梯度提升决策树(GBDT)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.2%20GBDT/3.2%20GBDT.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [3.3 XGBoost](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.3%20XGBoost/3.3%20XGBoost.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [3.4 LightGBM](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.4%20LightGBM/3.4%20LightGBM.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [4. 支持向量机(SVM)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/4.%20SVM/4.%20SVM.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [1. 线性回归(Liner Regression)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/Liner%20Regression/1.Liner%20Regression.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [2. 逻辑回归(Logistics Regression)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/2.Logistics%20Regression/2.Logistics%20Regression.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [3. 决策树(Desision Tree)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.Desition%20Tree/Desition%20Tree.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [3.1 随机森林(Random Forest)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.1%20Random%20Forest/3.1%20Random%20Forest.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [3.2 梯度提升决策树(GBDT)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.2%20GBDT/3.2%20GBDT.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [3.3 XGBoost](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.3%20XGBoost/3.3%20XGBoost.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [3.4 LightGBM](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/3.4%20LightGBM/3.4%20LightGBM.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [4. 支持向量机(SVM)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/4.%20SVM/4.%20SVM.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | 5. 概率图模型(Probabilistic Graphical Model) | | |
| 机器学习 | [5.1 贝叶斯网络(Bayesian Network)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/5.1%20Bayes%20Network/5.1%20Bayes%20Network.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [5.2 马尔科夫(Markov)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/5.2%20Markov/5.2%20Markov.md) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [5.1 贝叶斯网络(Bayesian Network)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/5.1%20Bayes%20Network/5.1%20Bayes%20Network.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [5.2 马尔科夫(Markov)](https://github.com/NLP-LOVE/ML-NLP/blob/master/Machine%20Learning/5.2%20Markov/5.2%20Markov.md) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | 5.3 主题模型(Topic Model) | | |
| 机器学习 | [6.最大期望算法(EM)](https://github.com/NLP-LOVE/ML-NLP/tree/master/Machine%20Learning/6.%20EM) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | [7.聚类(Clustering)](https://github.com/NLP-LOVE/ML-NLP/tree/master/Machine%20Learning/7.%20Clustering) | [@mantchs](https://github.com/mantchs) | 448966528 |
| 机器学习 | 8.ML特征工程和优化方法 | | |
| 机器学习 | [6.最大期望算法(EM)](https://github.com/NLP-LOVE/ML-NLP/tree/master/Machine%20Learning/6.%20EM) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [7.聚类(Clustering)](https://github.com/NLP-LOVE/ML-NLP/tree/master/Machine%20Learning/7.%20Clustering) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | [8.ML特征工程和优化方法](https://github.com/NLP-LOVE/ML-NLP/tree/master/Machine%20Learning/8.%20ML%E7%89%B9%E5%BE%81%E5%B7%A5%E7%A8%8B%E5%92%8C%E4%BC%98%E5%8C%96%E6%96%B9%E6%B3%95) | [@mantchs](https://github.com/NLP-LOVE) | 448966528 |
| 机器学习 | 9.sklearn工具使用 | | |
| 深度学习 | 10.神经网络(Neural Network) | | |
| 深度学习 | 11. 卷积神经网络(CNN) | | |
......
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