Machine Learning with BigQuery ML: Training Time Series Forecasting Models
BigQuery ML 2023
| Intermediate
- 8 videos | 57m 26s
- Includes Assessment
- Earns a Badge
Time series forecasting uses data collected over periodic intervals to understand and analyze how the variable changes over time. Time series analysis is used for forecasting problems, such as demand forecasting and revenue forecasting. The auto-regressive integrated moving average (ARIMA) model is widely used for time series forecasting. In this course, you will see how time series analysis works and how models such as the ARIMA model can help you forecast future values of time-varying data using historical values. You will also learn the differences between stationary and non-stationary time series data. Next, you will load and explore your time series data for store revenue prediction into BigQuery and visualize and explore this data using Looker Studio. Finally, you will use an ARIMA model to make revenue forecasts. You will see how BigQuery ML trains multiple ARIMA models to find the best auto-regressive, differencing, and moving average parameters for your data. You will also perform multiple time-series analysis by forecasting store revenue by region.
WHAT YOU WILL LEARN
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Discover the key concepts covered in this courseProvide an overview of time series analysisVisualize time series data in bigqueryQuery and visualize data
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Perform time series forecasting using an autoregressive integrated moving average (arima)Perform windowing on time series dataPerform multiple time series analysis for different categoriesSummarize the key concepts covered in this course
IN THIS COURSE
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1m 52sIn this video, we will discover the key concepts covered in this course. FREE ACCESS
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6m 36sAfter completing this video, you will be able to provide an overview of time series analysis. FREE ACCESS
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8m 28sIn this video, you will learn how to visualize time series data in BigQuery. FREE ACCESS
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11m 52sFind out how to query and visualize data. FREE ACCESS
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9m 33sIn this video, discover how to perform time series forecasting using an autoregressive integrated moving average (ARIMA). FREE ACCESS
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7m 46sLearn how to perform windowing on time series data. FREE ACCESS
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9m 20sDiscover how to perform multiple time series analysis for different categories. FREE ACCESS
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1m 58sIn this video, we will summarize the key concepts covered in this course. FREE ACCESS
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