📁 Kaggle实战班
  📁 七月kaggle
  📁 july七月Kaggle
    📁 课件
    📁 代码
    📄 第04课_kaggle案例实战班【】.mp4
    📄 第05课_kaggle案例实战班【】.mp4
    📄 第08课_kaggle案例实战班【】.mp4
    📄 第二节【】.mp4
    📄 第07课_kaggle案例实战班【】.mp4
    📄 第06课_kaggle案例实战班【】.mp4
    📄 第03课_kaggle案例实战班【】.mp4
    📄 1.机器学习解决问题综述课【】.mp4
    📄 9.贪心法和动态规划【】.mp4
    📄 5.链表递归栈【】.mp4
    📄 4.树【】.mp4
    📄 7.图论（上）【】.mp4
    📄 julyedu【】.com 解压密码
    📄 6.查找排序【】.mp4
    📄 8.图论下【】.mp4
    📄 10.概率分治和机器学习【】.mp4
      📁 lecture07
      📁 lecture03
      📁 lecture08
      📁 lecture06
      📁 lecture02
      📁 lecture01
      📁 lecture04
      📁 lecture05
      📁 lecture01
      📁 lecture07
      📁 lecture03
      📁 lecture08
      📁 lecture04
      📁 lecture05
      📁 lecture02
      📄 Kaggle第06课：走起~深度学习【】.pptx
      📄 Kaggle第05课：能源预测与分配问题【】.pdf
      📄 Kaggle第06课：走起~深度学习【】.pdf
        📄 Rossmann_Store_Sales_competition【】.ipynb
        📄 data【】.zip
        📄 Kaggle event recommendation competition【】.ipynb
        📄 kaggle-event-recommendation-rank1【】.zip
        📄 PPD_RiskControl_Competition【】.zip
        📄 search_ads_feature【】.sample
        📄 search_click_data【】.sample
        📄 feature_map【】.search_ads
        📄 feature【】.search_ads
        📄 avazu-CTR-Prediction-LR【】.zip
        📄 kaggle-avazu-rank1【】.zip
        📄 kaggle-avazu-rank2【】.zip
        📄 xgb_ads【】.conf
        📄 feature【】.search
        📄 generate_train_feature_reducer【】.py
        📄 generate_train_feature_mapper【】.py
        📄 Spark-Criteo-CTR-Prediction【】.ipynb
        📁 猫狗的数据
        📁 img
        📄 cat_dog【】.html
        📄 Kaggle第06课：走起~深度学习【】.pdf
        📄 image_search【】.html
        📄 char_rnn【】.html
        📄 word_rnn【】.html
        📄 Kaggle第06课：走起~深度学习【】.pptx
        📄 news_stock_advanced【】.html
        📄 energy_forecasting_notebooks【】.zip
        📄 subway_prediction_notebook【】.zip
        📁 input数据太大。就不传了。自己下载吧~ - 老师留
        📁 notebook
        📁 Feature_engineering_and_model_tuning
        📄 blending【】.py
        📄 Feature_engineering_and_model_tuning【】.zip
        📄 cs228-python-tutorial【】.ipynb
        📁 news stock
        📁 house price
        📄 第8课：金融风控问题【】.pdf
        📄 金融风控大赛解决方案【】.pdf
        📄 Kaggle第01课：机器学习算法、工具与流程概述【】.pdf
        📄 分享的链接【】.txt
        📄 kaggle-2014-criteo【】.pdf
        📄 predicting-clicks-facebook【】.pdf
        📄 百度凤巢：DNN在凤巢CTR预估中的应用【】.pdf
        📄 腾讯广点通：效果广告中的机器学习技术【】.pdf
        📄 第3课--排序与CTR预估【】.pdf
        📄 kaggle-avazu【】.pdf
        📄 从FM到FFM【】.pdf
        📄 阿里妈妈：大数据下的广告排序技术及实践【】.pdf
        📄 京东电商广告和推荐系统的机器学习系统实践【】.pdf
        📄 第7课：推荐与销量预测相关问题【】.pdf
          📄 cats-vs-dogs【】.txt
          📄 train【】.zip
          📄 test【】.zip
          📄 sample_submission【】.csv
        📄 第5课：能源预测与分配问题【】.pdf
        📄 Kaggle第四课【】.pdf
        📄 Kaggle第02课：经济金融相关问题【】.pdf
          📁 Kaggle-Bicycle-Example
          📁 Kaggle_Titanic
          📁 Feature-engineering_and_Parameter_Tuning_XGBoost
          📄 chi_square【】.png
          📄 RGBHistogram【】.jpg
          📁 .ipynb_checkpoints
          📄 search relevance【】.ipynb
          📄 search relevance_advanced【】.ipynb
          📄 news_stock【】.html
          📄 news_stock_advanced【】.html
          📄 search+relevance_advanced【】.html
          📄 search+relevance【】.html
          📁 input
          📁 _ipynb_checkpoints
          📁 notebook
            📁 .ipynb_checkpoints
            📄 test【】.csv
            📄 train【】.csv
            📄 Titanic【】.ipynb
          📁 notebook
          📁 input
          📁 _ipynb_checkpoints
          📄 data_description【】.txt
            📁 .ipynb_checkpoints
            📁 Kaggle_Bicycle_Example_files
            📄 kaggle_bike_competition_train【】.csv
            📄 Kaggle_Bicycle_Example【】.ipynb
            📄 search relevance_advanced-checkpoint【】.ipynb
            📄 search relevance-checkpoint【】.ipynb
            📄 RedditNews【】.csv
            📄 DJIA_table【】.csv
            📄 Combined_News_DJIA【】.csv
            📁 .ipynb_checkpoints
            📄 Test【】.csv
            📄 test_modified【】.csv
            📄 train_modified【】.csv
            📄 XGBoost models tuning【】.ipynb
            📄 Train【】.csv
            📄 Feature Engineering【】.ipynb
            📄 test【】.csv
            📄 sample_submission【】.csv
            📄 train【】.csv
            📁 .ipynb_checkpoints
            📄 news_stock【】.html
            📄 news_stock【】.ipynb
            📁 .ipynb_checkpoints
            📄 house_price_advanced【】.html
            📄 house_price【】.html
            📄 house_price_advanced【】.ipynb
            📄 house_price【】.ipynb
              📄 Titanic-checkpoint【】.ipynb
              📄 Kaggle_Bicycle_Example-checkpoint【】.ipynb
              📄 Kaggle_Bicycle_Example_46_1【】.png
              📄 Kaggle_Bicycle_Example_44_0【】.png
              📄 Kaggle_Bicycle_Example_34_0【】.png
              📄 Kaggle_Bicycle_Example_47_1【】.png
              📄 Kaggle_Bicycle_Example_43_0【】.png
              📄 Kaggle_Bicycle_Example_42_0【】.png
              📄 Kaggle_Bicycle_Example_49_1【】.png
              📄 Kaggle_Bicycle_Example_45_0【】.png
              📄 XGBoost models tuning-checkpoint【】.ipynb
              📄 Feature Engineering-checkpoint【】.ipynb
              📄 news_stock-checkpoint【】.ipynb
              📄 house_price_advanced-checkpoint【】.ipynb
              📄 house_price-checkpoint【】.ipynb