[NeurIPS 2024 Spotlight] Official repository of the CycleNet paper: "CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns". This work is developed by the Lab of Professor Weiwei Lin (linww@scut.edu.cn), South China University of Technology; Peng Cheng Laboratory. (2024-09-27, Jupyter Notebook, 0KB, 下载0次)
http://www.pudn.com/Download/item/id/1727415550865719.html
执行探索性数据分析（EDA），以发现模式、趋势和见解，从而帮助零售企业做出明智的决策。在数据清理、探索性数据分析、解释描述性统计、时间序列分析、有效沟通见解的数据可视化方面获得了动手经验。
Performed exploratory data analysis (EDA) to uncover patterns, trends, and insights that can help the retail business make informed decisions. Gained hands-on experience in data cleaning, exploratory data analysis, interpreting descriptive statistics, time series analysis, data visualization for effective communication of insights. (2024-07-15, Jupyter Notebook, 0KB, 下载0次)
美国县域微型企业的时间序列分析
Time series analysis of microbusinesses in counties of USA (2024-03-15, Jupyter Notebook, 0KB, 下载0次)
回购能够使用ARIMA和其他时间序列方法进行准确的客户收入预测。它提供了实际示例、数据预处理、评估和优化。它还通过市场分析和预测建模来识别潜在客户。增强企业的数据驱动增长能力。
The repo enables accurate customer revenue forecasting using ARIMA and other time series methods. It provides practical examples, data preprocessing, evaluation, and optimization. It also identifies potential customers through market analysis and predictive modeling. Empowering businesses for data-driven growth. (2024-03-13, Jupyter Notebook, 0KB, 下载0次)
该库的建立是为了分析和预测萨尔城大气污染物浓度的时间序列…
This repository was created for the analysis and prediction of time series of concentrations of atmospheric pollutants in the city of Sal… (2024-01-22, Jupyter Notebook, 0KB, 下载0次)
对美国空气污染进行了全面的时间序列分析（2000-2015），强调CO对臭氧的影响。研究结果为决策者、经济学家和企业提供信息，为有效监管和可持续实践提供见解
Conducted a comprehensive time series analysis (2000-2015) on U.S. air pollution, emphasizing CO s impact on ozone. Findings inform policymakers, economists, and businesses, offering insights for effective regulations and sustainable practices (2023-12-23, Jupyter Notebook, 0KB, 下载0次)
时间序列分析-该项目的主要目标是预测信实工业有限公司（Reliance Industries Limited）在未来几年的股价...
Time Series Analysis -The main objective of the project is to predict the stock prices of Reliance Industries Limited for the upcoming days. This involves obtaining essential stock data such as Open, High, Low, and Close prices, from 2015 to 2020. The project aims to identify short-term and long-term trends, analyze the impact (2023-11-28, Jupyter Notebook, 0KB, 下载0次)
[ECML PKDD 2023]用于企业异常检测的上下文感知深度时间序列分解，
[ECML PKDD 2023] Context-Aware Deep Time-Series Decomposition for Anomaly Detection in Businesses, (2023-09-19, Jupyter Notebook, 0KB, 下载0次)