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https://github.com/solidglue/machine_learning_sklearn_examples

机器学习Sklearn入门指南。Machine Learning Sklearn API and Examples with Python3 and Jupyter Notebook.
https://github.com/solidglue/machine_learning_sklearn_examples
machine-learning sklearn
Last synced: 27 days ago
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机器学习Sklearn入门指南。Machine Learning Sklearn API and Examples with Python3 and Jupyter Notebook.
Host: GitHub
URL: https://github.com/solidglue/machine_learning_sklearn_examples
Owner: solidglue
License: apache-2.0
Created: 2024-02-28T10:25:48.000Z (8 months ago)
Default Branch: master
Last Pushed: 2024-05-20T09:17:34.000Z (6 months ago)
Last Synced: 2024-10-10T08:20:23.989Z (27 days ago)
Topics: machine-learning, sklearn
Language: Jupyter Notebook
Homepage:
Size: 2.59 MB
Stars: 109
Watchers: 2
Forks: 2
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project

README

        # 机器学习Sklearn入门指南

机器学习入门指南，基于SKlearn讲解如何学习《机器学习》，更新中。 

## 注意

如果通过Github站内超链接打开Jupyter Notebook文件发生错误，可以点击根据 https://nbviewer.org 生成的“备用链接”间接访问对应文件。  

或者通过以下链接访问整个项目的站外备用链接，注意点击站外备用链接里的非Jupyter Notebook格式文件会跳转回到Github仓库内：  

●  [**Machine_Learning_Sklearn_Examples**](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/tree/master/)  

## 机器学习Python基础  

●  [**Numpy科学计算**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_01_Numpy_basic.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_01_Numpy_basic.ipynb)]    

●  [**Pandas数据分析**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_02_Pandas_basic.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_02_Pandas_basic.ipynb)]      

●  [**Matplotlib可视化**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_03_Matplotlib_basic.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_03_Matplotlib_basic.ipynb)]       

●  [**数据探索EDA**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_04_EDA.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/00_Python_basics/00_04_EDA.ipynb)]       

## 监督学习

●  [**线性回归**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_01_Linear_regression.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_01_Linear_regression.ipynb)]      

●  [**逻辑回归**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_02_Logistic_regression.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_02_Logistic_regression.ipynb)]      

●  [**支持向量机SVM**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_03_Svm.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_03_Svm.ipynb)]       

●  随机梯度下降SGD  

●  [**K近邻（KNN）**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_05_Knn.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_05_Knn.ipynb)]      

●  朴素贝叶斯  

●  [**决策树**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_07_Decision_trees.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_07_Decision_trees.ipynb)]      

●  [**随机森林**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/01_Supervised_learning/01_08_Random_forests.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/01_Supervised_learning/01_08_Random_forests.ipynb)]      

●  多分类与多输出  

●  特征选择  

●  神经网络  

## 无监督学习

●  [**Kmeans聚类**](https://github.com/solidglue/Machine_Learning_Sklearn_Jupyter_Demo/blob/master/02_Unsupervised_learning/02_01_Kmeans_clustering.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/02_Unsupervised_learning/02_01_Kmeans_clustering.ipynb)]        

●  神经网络模型（无监督）  

## 模型选择与评估

●  [**交叉验证**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_01_Cross_validation.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_01_Cross_validation.ipynb)]      

●  [**调整估算器超参数**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_02_hyper_parameters_estimator.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_02_hyper_parameters_estimator.ipynb)]      

●  [**指标和评分**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_03_Metrics_and_scoring.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_03_Metrics_and_scoring.ipynb)]      

●  [**验证曲线：绘制分数以评估模型**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_04_Validation_curves.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/03_Model_selection_and_evaluation/03_04_Validation_curves.ipynb)]      

## 可视化

●  可视化  

## 数据集转换

●  [**流水线和复合估算器**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_01_Pipelines_and_composite_estimators.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_01_Pipelines_and_composite_estimators.ipynb)]      

●  [**特征提取**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_02_Feature_extraction.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_02_Feature_extraction.ipynb)]      

●  [**数据预处理**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_03_Preprocessing_data.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_03_Preprocessing_data.ipynb)]      

●  [**缺失值补充**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_04_Imputation_of_missing_values.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/05_Dataset_transformations/05_04_Imputation_of_missing_values.ipynb)]      

●  无监督降维  

●  随机投影  

## 数据集加载

●  [**玩具数据集**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_01_Toy_datasets.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_01_Toy_datasets.ipynb)]      

●  [**真实世界数据集**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_02_Real_world_datasets.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_02_Real_world_datasets.ipynb)]      

●  [**生成的数据集**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_03_Generated%20datasets.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_03_Generated%20datasets.ipynb)]      

●  [**加载其他数据集**](https://github.com/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_04_load_files.ipynb)       [~~*(备用链接)*~~](https://nbviewer.org/github/solidglue/Machine_Learning_Sklearn_Examples/blob/master/06_Dataset_loading/06_04_load_files.ipynb)]      

## 模型持久化

●  模型持久化  

## *扩展

1.**推荐系统**  

王树森推荐系统公开课 - 基于小红书的场景讲解工业界真实的推荐系统。  

●  [**Recommender_System**](https://github.com/solidglue/Recommender_System) 

2.**YouTuBe推荐系统排序模型**  

以"DNN_for_YouTube_Recommendations"模型和电影评分数据集（ml-1m）为基础，详尽的展示了如何基于TensorFlow2实现推荐系统排序模型。  

●  [**YouTube深度排序模型(多值embedding、多目标学习)**](https://github.com/solidglue/DNN_for_YouTube_Recommendations) 

3.**推荐系统推理服务**  

基于Goalng、Docker和微服务思想实现了高并发、高性能和高可用的推荐系统推理微服务，包括多种召回/排序服务，并提供多种接口访问方式（REST、gRPC和Dubbo）等，每日可处理上千万次推理请求。   

● [**推荐系统推理微服务Golang**](https://github.com/solidglue/Recommender_System_Inference_Services)  

4.**深度学习TensorFlow入门教程**  

●  [**深度学习TensorFlow入门教程**](https://github.com/solidglue/Deep_Learning_TensorFlow2_Examples)