Predict future sales using CSV data and date range
Analyze stock financial data and forecasts
使用 Prophet 來預測股價, 如台積電輸入 2330.tw
Forecast future values from time series data
Optimal Selling Strategy for Farmers
Predict stock prices and trade using LSTM model
Fetch stock data, predict future trends, and get investment advice
Analyse stock trends and predict future prices
Visualize stock price targets and trends
Stock market prediction specially for Indian Index
Detect similar stock price patterns
du bao chung khoan
Predict Google stock prices using LSTM
Forecast TimeSeries Sales is an AI-powered tool designed to predict future sales trends using historical data. It leverages CSV data and a specified date range to generate accurate forecasts, helping businesses make informed decisions. This tool is ideal for organizations looking to anticipate market demands, optimize inventory, and plan resources effectively.
• Data Input: Accepts historical sales data in CSV format. • Date Range Selection: Users can specify a time range for forecasting. • Multiple Models: Utilizes advanced algorithms to ensure high accuracy. • Accuracy Metrics: Provides confidence intervals and error margins. • Trend Analysis: Identifies patterns and seasonality in sales data. • Scalability: Works with small or large datasets. • Customizable Dashboards: Visualizes forecasts and historical data.
• What data format do I need to use?
You must use CSV files containing at least two columns: one for dates and one for sales data.
• How far into the future can I forecast?
The tool allows forecasting up to 12 months based on your selected date range.
• Can I customize the forecast model?
Yes, you can tweak parameters such as the model type, seasonality, and trend settings.
• How accurate are the forecasts?
Accuracy depends on data quality and historical patterns, with most forecasts achieving 85-95% accuracy.
• Can I export the forecast data?
Yes, you can export it as CSV or view it in a dashboard for easier sharing and analysis.