Use Prophet para detecção de anomalias e consulte com Chatbot
Detect financial transaction anomalies and get expert insights
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Detect anomalies in Excel data
Detect anomalies in images
Configure providers to generate a Stremio manifest URL
Detect anomalies in credit card transaction data
Visualize anomaly detection results across different datasets
Detect anomalies in time series data
Detect anomalies in images
Detect adversarial examples using neighborhood relations
Classify images as normal or anomaly
Implement using models like Isolation Forest/Local Outlier.
Streamlit Chatbot is an open-source tool designed for anomaly detection using Facebook Prophet. It combines powerful time-series forecasting capabilities with an interactive chatbot interface to help users analyze and understand data patterns. This tool is ideal for real-time data analysis and provides a user-friendly way to interact with complex data insights.
pip install streamlit prophet in your terminal.streamlit run your_script.py.What is Facebook Prophet?
Facebook Prophet is an open-source forecasting tool developed by Facebook (now Meta). It is specifically designed for time-series data and is known for its simplicity and accuracy in handling multiple seasonality with non-linear trends.
What kind of data can I analyze with Streamlit Chatbot?
You can analyze any time-series data with a timestamp and value column. Common use cases include website traffic, sales data, sensor readings, and more.
Can I customize the chatbot's responses?
Yes, the chatbot's responses can be customized to better suit your specific use case. You can modify the underlying logic or integrate custom anomaly detection rules as needed.