SARIMA
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Explore more → **SARIMA**
What is SARIMA?
SARIMA (Seasonal Autoregressive Integrated Moving Average) is a statistical method used for analyzing and forecasting time series data that exhibits seasonality. It extends the ARIMA model to explicitly account for seasonal patterns in the data. It is commonly used in economics, finance, and environmental science to predict future values based on historical observations.
What other technologies are related to SARIMA?
SARIMA Competitor Technologies
ARIMA
ARIMA models are a specific case of SARIMA models, for time series data without seasonality. Therefore, they compete in the same application space.
LSTMs
LSTMs are a type of recurrent neural network often used for time series forecasting, providing an alternative approach to SARIMA.
LSTM
LSTM is a type of recurrent neural network often used for time series forecasting, providing an alternative approach to SARIMA.
Prophet
Prophet is a forecasting procedure, also used to model time series data with seasonality, much like SARIMA.
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SARIMA Complementary Technologies
GCP Vertex AI
GCP Vertex AI is a machine learning platform that can be used to train and deploy SARIMA models.
scikit-learn
Scikit-learn provides tools and algorithms that can be used to build and evaluate SARIMA models.
Pandas
Pandas is a data manipulation library often used to prepare time series data for SARIMA modeling.
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Which job functions commonly mention SARIMA?
Data Scientist
0.1% of all Data Scientist jobs mention SARIMA
View 124
jobs on Sumble
Machine Learning
49 Machine Learning jobs mention SARIMA
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jobs on Sumble
AI Engineer
20 AI Engineer jobs mention SARIMA
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jobs on Sumble
DevSecOps Engineer
2 DevSecOps Engineer jobs mention SARIMA
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jobs on Sumble
Solutions Architect
5 Solutions Architect jobs mention SARIMA
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jobs on Sumble
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