Time Series Forecasting Samples
Explore practical examples and best practices for implementing time series forecasting solutions on Azure AI/ML.
Introduction to Time Series Forecasting
Learn the fundamental concepts of time series analysis and build your first forecasting model with Azure ML. Covers data preparation, feature engineering, and basic model selection.
Advanced Forecasting Models
Dive into more complex forecasting techniques like ARIMA, Prophet, and deep learning models (LSTM, Transformers) for handling seasonality, trend, and irregular patterns.
MLOps for Time Series Forecasting
Implement robust MLOps practices for your forecasting pipelines. Includes automated retraining, deployment strategies, and monitoring of live models on Azure.
Anomaly Detection in Time Series
Learn how to identify unusual patterns and outliers in your time series data using Azure AI/ML tools and techniques, crucial for event detection and system health monitoring.
Real-time Forecasting
Build streaming forecasting solutions that can predict future values as new data arrives, essential for dynamic applications and operational decision-making.
Scalable Forecasting Solutions
Optimize your forecasting workflows for large datasets and high-volume predictions using distributed computing and Azure's scalable infrastructure.