配套代码和数据集《跟着迪哥学 Python数据分析与机器学习实战》

Rita2029

496

收藏 2025-01-15

详细“目录清单”供下载前参考！！

目录清单.pdf
大小:(992.2 KB)

马上下载

第16章：聚类实例
第20章：LSTM情感分析
第18章：Tensorflow框架实战
第15章：降维算法
第14章：打造音乐推荐系统
第12章：支持向量机
第11章：新闻分类实战
第10章：特征工程
第9章：随机森林气温预测
第6章：信用卡欺诈检测
第4章：Matplotlib
第3章：Pandas
第2章：Numpy

+第9章：随机森林气温预测          6.3 MB
+随机森林          6.3 MB
+随机森林             6.3 MB
tree2.png             795.0 KB
tree.png             795.0 KB
tree.dot             19.1 KB
small_tree.png             56.1 KB
small_tree.dot             1.3 KB
rf_drawings.docx             372.0 KB
3-随机森林参数选择.ipynb             24.8 KB
2-数据与特征对随机森林的影响.ipynb             737.0 KB
1-随机森林.ipynb             244.0 KB
  +images             2.2 MB
  +data             102.0 KB
temps_extended.csv             91.1 KB
temps.csv             11.0 KB
  +.ipynb_checkpoints             1.0 MB
3-随机森林参数选择-checkpoint.ipynb             24.8 KB
2-数据与特征对随机森林的影响-checkpoint.ipynb             733.0 KB
1-随机森林-checkpoint.ipynb             241.0 KB
+第6章：信用卡欺诈检测          144.0 MB
+逻辑回归-信用卡欺诈检测          144.0 MB
  逻辑回归-信用卡检测任务.ipynb             163.0 KB
  test.png             22.5 KB
  creditcard.csv             144.0 MB
+.ipynb_checkpoints             163.0 KB
逻辑回归-信用卡检测任务-checkpoint.ipynb             163.0 KB
+第4章：Matplotlib          4.9 MB
+Matplotlib绘图          4.9 MB
  8-Pandas与sklearn结合实例.ipynb             219.0 KB
  7-pie与布局.ipynb             339.0 KB
  6-3D图.ipynb             579.0 KB
  5-直方图and散点图.ipynb             217.0 KB
  4-盒图.ipynb             117.0 KB
  3-条形图.ipynb             826.0 KB
  2-风格设置.ipynb             226.0 KB
  1-Matplotlib基本操作.ipynb             484.0 KB
+img             1.9 MB
+第3章：Pandas          148.0 MB
+Pandas代码          148.0 MB
  titanic_train.csv             59.8 KB
  tips.csv             7.8 KB
  Pandas练习题.ipynb             59.4 KB
  macrodata.csv             17.8 KB
  game_logs.csv             130.0 MB
  9-pivot操作.ipynb             24.7 KB
  8-显示设置.ipynb             6.3 KB
  7-merge合并.ipynb             29.0 KB
  7-merge操作.ipynb             29.0 KB
  6-对象操作.ipynb             29.5 KB
  5-数值运算.ipynb             24.0 KB
  4-基础结构.ipynb             605 Byte
  3-groupby.ipynb             7.9 KB
  2-Pandas索引.ipynb             43.4 KB
  1-Pandas-介绍.ipynb             34.9 KB
  17-apply操作.ipynb             12.2 KB
  16-大数据处理技巧.ipynb             25.2 KB
  16-大数据处理.ipynb             24.8 KB
  15-Pandas绘图.ipynb             207.0 KB
  14-索引2.ipynb             27.6 KB
  13-字符串操作.ipynb             14.7 KB
  12-groupby练习.ipynb             41.5 KB
  11-常用操作.ipynb             38.1 KB
  10-时间操作.ipynb             220.0 KB
+data             17.3 MB
  titanic.csv             59.8 KB
  FR040370000800100hour.1-1-1999.31-12-2012             1.1 MB
  FR040120000800100hour.1-1-1999.31-12-2012             1.1 MB
  flowdata.csv             854.0 KB
  BETR8010000800100hour.1-1-1990.31-12-2012             1.9 MB
  BETN0290000800100hour.1-1-1990.31-12-2012             1.8 MB
  airbase_data.csv             4.8 MB
  20000101_20161231-NO2.csv             5.7 MB
+.ipynb_checkpoints             261.0 KB
8-显示设置-checkpoint.ipynb             6.3 KB
1-Pandas-介绍-checkpoint.ipynb             34.9 KB
10-时间操作-checkpoint.ipynb             220.0 KB
+第2章：Numpy          121.0 KB
+numpy代码          121.0 KB
练习题.ipynb             22.5 KB
9-读写.ipynb             7.6 KB
8-随机模块.ipynb             5.6 KB
7-运算.ipynb             7.3 KB
6-数组生成.ipynb             10.6 KB
5-数组形状.ipynb             11.8 KB
4-排序.ipynb             5.2 KB
3-数值计算.ipynb             11.4 KB
2-array结构.ipynb             20.3 KB
1-Numpy概述.ipynb             6.5 KB
+.ipynb_checkpoints             11.8 KB
  5-数组形状-checkpoint.ipynb             11.8 KB
+.ipynb_checkpoints          72 Byte
  Untitled-checkpoint.ipynb             72 Byte
+第20章：LSTM情感分析          159.0 MB
+LSTM情感分析          159.0 MB
  LSTM.ipynb             59.2 KB
+training_data             158.0 MB
  wordVectors.npy             76.3 MB
  wordsList.npy             25.9 MB
  idsMatrix.npy             23.8 MB
+positiveReviews             16.1 MB
+negativeReviews             15.5 MB
+Images             1.0 MB
+.ipynb_checkpoints             58.6 KB
LSTM-checkpoint.ipynb             58.6 KB
+第18章：Tensorflow框架实战          12.4 MB
+Tensorflow          12.4 MB
  6-卷积神经网络.ipynb             6.2 KB
  5-神经网络.ipynb             7.9 KB
  4-逻辑回归.ipynb             7.1 KB
  3-Mnist数据集.ipynb             38.3 KB
  2-线性回归.ipynb             55.7 KB
  1-基本结构.ipynb             8.7 KB
+img             1.2 MB
+data             11.1 MB
train-labels-idx1-ubyte.gz             28.2 KB
train-images-idx3-ubyte.gz             9.5 MB
t10k-labels-idx1-ubyte.gz             4.4 KB
t10k-images-idx3-ubyte.gz             1.6 MB
+第16章：聚类实例          906.0 KB
+聚类实例          906.0 KB
+聚类算法             906.0 KB
kmeans-dbscan.ipynb             420.0 KB
data.txt             610 Byte
1.png             65.3 KB
  +.ipynb_checkpoints             420.0 KB
kmeans-dbscan-checkpoint.ipynb             420.0 KB
+第15章：降维算法          676.0 KB
+降维算法          676.0 KB
+PCA             327.0 KB
  PCA.ipynb             142.0 KB
  iris.data             4.6 KB
+.ipynb_checkpoints             181.0 KB
PCA-checkpoint.ipynb             181.0 KB
+LDA             348.0 KB
LDA.ipynb             80.6 KB
7.png             8.9 KB
6.png             22.9 KB
5.png             25.9 KB
4.png             26.0 KB
3.png             12.8 KB
2.png             6.6 KB
1.png             16.7 KB
  +.ipynb_checkpoints             148.0 KB
LDA-checkpoint.ipynb             148.0 KB
+第14章：打造音乐推荐系统          4.2 GB
+Python实现音乐推荐系统          4.2 GB
  推荐系统.ipynb             366.0 KB
  user_playcount_df.csv             44.1 MB
  triplet_dataset_sub_song.csv             648.0 MB
  train_triplets.txt             2.8 GB
  track_metadata_df_sub.csv             5.9 MB
  track_metadata.db             712.0 MB
  song_playcount_df.csv             8.5 MB
  Recommenders.py             9.2 KB
  recommendation_engines.py             13.4 KB
  8.png             68.8 KB
  7.png             77.3 KB
  6.png             60.3 KB
  5.png             3.6 KB
  4.png             12.0 KB
  3.png             43.0 KB
  2.png             30.4 KB
  1.png             45.3 KB
+__pycache__             5.0 KB
+.ipynb_checkpoints             364.0 KB
推荐系统-checkpoint.ipynb             364.0 KB
+第12章：支持向量机          3.1 MB
+支持向量机          3.1 MB
+支持向量机-图书             3.1 MB
  +notebooks             3.1 MB
support_vector_machines修改.ipynb             812.0 KB
  +.ipynb_checkpoints             2.3 MB
support_vector_machines修改-checkpoint.ipynb                812.0 KB
support_vector_machines-checkpoint.ipynb                1.5 MB
  +images             71.8 KB
+第11章：新闻分类实战          420.0 KB
+贝叶斯新闻分类任务          420.0 KB
  新闻分类任务.ipynb             179.0 KB
  四川大学机器智能实验室停用词库.txt             8.4 KB
  哈工大停用词表.txt             5.9 KB
  stwords.txt             5.6 KB
  stopwords.txt             17.3 KB
  stopwords.data             24.5 KB
+.ipynb_checkpoints             179.0 KB
新闻分类任务-checkpoint.ipynb             179.0 KB
+第10章：特征工程          6.1 MB
+数值特征          6.1 MB
文本特征.ipynb             42.7 KB
图像特征.ipynb             259.0 KB
数值特征.ipynb             231.0 KB
  +datasets             4.2 MB
vgsales.csv             1.3 MB
song_views.csv             27.8 KB
Pokemon.csv             46.9 KB
item_popularity.csv             147 Byte
fcc_2016_coder_survey_subset.csv             2.6 MB
dog.png             54.6 KB
desktop.ini             138 Byte
cat.png             120.0 KB
  +.ipynb_checkpoints             1.4 MB
文本特征-checkpoint.ipynb             42.5 KB
图像特征-checkpoint.ipynb             792.0 KB
特征预处理-checkpoint.ipynb             11.7 KB
数值特征-checkpoint.ipynb             217.0 KB
Feature Selection-checkpoint.ipynb             29.2 KB
Feature Engineering on Text Data-checkpoint.ipynb             47.6 KB
Feature Engineering on Temporal Data-checkpoint.ipynb             23.1 KB
Feature Engineering on Numeric Data-checkpoint.ipynb             239.0 KB

https://bbs.pinggu.org/thread-12592569-1-1.html
论坛里已经有了，版主不让发，删除了！