Pinned Repositories
2018_diantou_PhotovoltaicPowerStation
2018光伏发电预测比赛，结果a榜22/801 ，b榜44/801
competition_diantou_2018
2018比赛-大数据-光伏电站-人工智能运维
DC_PV_Power_Predict_2018
DataCastle 2018国能日新第一届光伏功率预测
Electric-Power-Hourly-Load-Forecasting-using-Recurrent-Neural-Networks
This project aims to predict the hourly electricity load in Toronto based on the loads of previous 23 hours using LSTM recurrent neural network.
flasky
Companion code to my O'Reilly book "Flask Web Development".
Household-electric-power-Forecasting-using-XGBoost
Household electric power Forecasting using XGBoost
JD_mobilephone_crawler
kaggle-book
Code Repository for The Kaggle Book, Published by Packt Publishing
Lihang
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
lihang-code
《统计学习方法》的代码实现
zhongtk's Repositories
zhongtk/2018_diantou_PhotovoltaicPowerStation
2018光伏发电预测比赛，结果a榜22/801 ，b榜44/801
zhongtk/competition_diantou_2018
2018比赛-大数据-光伏电站-人工智能运维
zhongtk/DC_PV_Power_Predict_2018
DataCastle 2018国能日新第一届光伏功率预测
zhongtk/Electric-Power-Hourly-Load-Forecasting-using-Recurrent-Neural-Networks
This project aims to predict the hourly electricity load in Toronto based on the loads of previous 23 hours using LSTM recurrent neural network.
zhongtk/flasky
Companion code to my O'Reilly book "Flask Web Development".
zhongtk/Household-electric-power-Forecasting-using-XGBoost
Household electric power Forecasting using XGBoost
zhongtk/JD_mobilephone_crawler
zhongtk/kaggle-book
Code Repository for The Kaggle Book, Published by Packt Publishing
zhongtk/Lihang
Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]
zhongtk/lihang-code
《统计学习方法》的代码实现
zhongtk/lihang_book_algorithm
致力于将李航博士《统计学习方法》一书中所有算法实现一遍
zhongtk/Machine-Learning-for-Solar-Energy-Prediction
Predict the Power Production of a solar panel farm from Weather Measurements using Machine Learning
zhongtk/pachong
一些爬虫的代码
zhongtk/photovoltaics
光伏发电功率预测
zhongtk/phv
光伏短期功率预测大赛 代码
zhongtk/Project-3-2019
数学建模：基于随机森林对光伏发电功率的预测
zhongtk/pydata-book
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
zhongtk/PythonCrawler
zhongtk/Short-Term-Wind-Speed-Prediction-based-on-Deep-Learning
LSTM neural network realizes the prediction of wind speed through the learning of various parameters. It can provide important support for the smooth operation of power system and the optimization of control strategy. The fuzzy rough set theory is used to reduce many factors that affect wind speed. It simplifies the input of the neural network prediction model and improves the accuracy and speed. Compared with the traditional neural network prediction method, MAE and MAPE in FRS-LSTM wind speed forecasting model have decreased and the accuracy has been improved greatly.
zhongtk/statistical-learning-method-solutions-manual
《统计学习方法》（第二版）习题解答，在线阅读地址：https://datawhalechina.github.io/statistical-learning-method-solutions-manual
zhongtk/Statistical-Learning-Method_Code
手写实现李航《统计学习方法》书中全部算法
zhongtk/wechat_jump_game
python 微信《跳一跳》辅助
zhongtk/XiaQian
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