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prophet

https://static.github-zh.com/github_avatars/dipanjanS?size=40

#自然语言处理#Master the essential skills needed to recognize and solve complex real-world problems with Machine Learning and Deep Learning by leveraging the highly popular Python Machine Learning Eco-system.

Jupyter Notebook 2.35 k
1 年前
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#时序数据库#Automatically build ARIMA, SARIMAX, VAR, FB Prophet and XGBoost Models on Time Series data sets with a Single Line of Code. Created by Ram Seshadri. Collaborators welcome.

Jupyter Notebook 760
1 年前
https://static.github-zh.com/github_avatars/moyuweiqing?size=40

(陆续更新)重新整理过的基于机器学习的股票价格预测算法,里面包含了基本的回测系统以及各种不同的机器学习算法的股票价格预测,包含:LSTM算法、Prophet算法、AutoARIMA、朴素贝叶斯、SVM、随机森林等

HTML 353
2 年前
https://static.github-zh.com/github_avatars/felipeangelimvieira?size=40
Python 65
6 天前
https://static.github-zh.com/github_avatars/JiaxiangBU?size=40

光伏短期功率预测大赛 代码

R 44
3 年前
https://static.github-zh.com/github_avatars/OmaymaS?size=40

#时序数据库#Shiny App that offers an interactive interface to explore the main functions of the [prophet Package](https://cran.r-project.org/package=prophet)

R 44
7 年前
https://static.github-zh.com/github_avatars/bits-bytes-nn?size=40
Jupyter Notebook 41
4 年前
https://static.github-zh.com/github_avatars/kennedyCzar?size=40

Predictive algorithm for forecasting the mexican stock exchange. Machine Learning approach to forecast price and Indicator behaviours of MACD, Bollinger and SuperTrend strategy

Python 39
3 年前
https://static.github-zh.com/github_avatars/zikrach?size=40

#时序数据库#Shiny app for Price Optimization using prophet and lme4 libraries for R.

R 37
7 年前
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