Time Series Forecasting with Machine Learning: Advanced Techniques

Introduction

Time series forecasting predicts future data points by analyzing patterns over time, critical for business planning.

Advanced Techniques

• Long Short-Term Memory (LSTM) networks for capturing long-term dependencies
• ARIMA models for traditional statistical forecasting
• Prophet by Facebook for easy-to-use forecasting with holidays and trends

Use Cases

Sales predictions, stock price forecasting, and resource allocation are common applications.

Conclusion

Combining ML techniques enhances accuracy and adaptability in time series forecasting.