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机器学习课程目录
第01课.机器学习解决问题综述课.mp4
第03课_kaggle案例实战班.mp4
第04课_kaggle案例实战班.mp4
第05课_kaggle案例实战班.mp4
第06课_kaggle案例实战班.mp4
第07课_kaggle案例实战班.mp4
第08课_kaggle案例实战班.mp4
第二节.mp4
<代码>
<lecture01>
blending.py
cs228-python-tutorial.ipynb
Feature_engineering_and_model_tuning.zip
<Feature_engineering_and_model_tuning>
<Feature-engineering_and_Parameter_Tuning_XGBoost>
Feature Engineering.ipynb
Test.csv
test_modified.csv
Train.csv
train_modified.csv
XGBoost models tuning.ipynb
<.ipynb_checkpoints>
Feature Engineering-checkpoint.ipynb
XGBoost models tuning-checkpoint.ipynb
<Kaggle_Titanic>
test.csv
Titanic.ipynb
train.csv
<.ipynb_checkpoints>
Titanic-checkpoint.ipynb
<Kaggle-Bicycle-Example>
Kaggle_Bicycle_Example.ipynb
kaggle_bike_competition_train.csv
<.ipynb_checkpoints>
Kaggle_Bicycle_Example-checkpoint.ipynb
<Kaggle_Bicycle_Example_files>
Kaggle_Bicycle_Example_34_0.png
Kaggle_Bicycle_Example_42_0.png
Kaggle_Bicycle_Example_43_0.png
Kaggle_Bicycle_Example_44_0.png
Kaggle_Bicycle_Example_45_0.png
Kaggle_Bicycle_Example_46_1.png
Kaggle_Bicycle_Example_47_1.png
Kaggle_Bicycle_Example_49_1.png
<lecture02>
<house price>
data_description.txt
<_ipynb_checkpoints>
<input>
sample_submission.csv
test.csv
train.csv
<notebook>
house_price.html
house_price.ipynb
house_price_advanced.html
house_price_advanced.ipynb
<.ipynb_checkpoints>
house_price_advanced-checkpoint.ipynb
house_price-checkpoint.ipynb
<news stock>
<_ipynb_checkpoints>
<input>
Combined_News_DJIA.csv
DJIA_table.csv
RedditNews.csv
<notebook>
news_stock.html
news_stock.ipynb
<.ipynb_checkpoints>
news_stock-checkpoint.ipynb
<lecture03>
avazu-CTR-Prediction-LR.zip
feature.search
feature.search_ads
feature_map.search_ads
generate_train_feature_mapper.py
generate_train_feature_reducer.py
kaggle-avazu-rank1.zip
kaggle-avazu-rank2.zip
search_ads_feature.sample
search_click_data.sample
Spark-Criteo-CTR-Prediction.ipynb
xgb_ads.conf
<lecture04>
<input数据太大。就不传了。自己下载吧~ - 老师留>
<notebook>
news_stock.html
news_stock_advanced.html
search relevance.ipynb
search relevance_advanced.ipynb
search+relevance.html
search+relevance_advanced.html
<.ipynb_checkpoints>
search relevance_advanced-checkpoint.ipynb
search relevance-checkpoint.ipynb
cture05>
energy_forecasting_notebooks.zip
subway_prediction_notebook.zip
<lecture06>
cat_dog.html
char_rnn.html
image_search.html
Kaggle第06课：走起~深度学习.pdf
Kaggle第06课：走起~深度学习.pptx
news_stock_advanced.html
word_rnn.html
<img>
chi_square.png
RGBHistogram.jpg
<猫狗的数据>
cats-vs-dogs.txt
sample_submission.csv
test.zip
train.zip
<lecture07>
data.zip
Kaggle event recommendation competition.ipynb
kaggle-event-recommendation-rank1.zip
Rossmann_Store_Sales_competition.ipynb
<lecture08>
PPD_RiskControl_Competition.zip
<课件>
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
Kaggle第06课：走起~深度学习.pptx
<lecture01>
Kaggle第01课：机器学习算法、工具与流程概述.pdf
分享的链接.txt
<lecture02>
Kaggle第02课：经济金融相关问题.pdf
<lecture03>
kaggle-2014-criteo.pdf
kaggle-avazu.pdf
predicting-clicks-facebook.pdf
阿里妈妈：大数据下的广告排序技术及实践.pdf
百度凤巢：DNN在凤巢CTR预估中的应用.pdf
从FM到FFM.pdf
第3课--排序与CTR预估.pdf
京东电商广告和推荐系统的机器学习系统实践.pdf
腾讯广点通：效果广告中的机器学习技术.pdf
<lecture04>
Kaggle第四课.pdf
<lecture05>
第5课：能源预测与分配问题.pdf
<lecture07>
第7课：推荐与销量预测相关问题.pdf
<lecture08>
第8课：金融风控问题.pdf
金融风控大赛解决方案.pdf
课程附带源码教程课件，教程下载地址：
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发表于 2019-4-13 10:10
