AI Show: Time Series Forecasting with Automated Machine Learning

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Building forecasts is an integral part of any business, whether it's revenue, inventory, sales, or customer demand. Building machine learning models is time-consuming and complex with many factors to consider, such as iterating through algorithms, tuning your hyperparameters and feature engineering. These choices multiply with time series data, with additional considerations of trends, seasonality, holidays and effectively splitting training data. Forecasting within automated machine learning (ML) takes these factors into consideration and includes capabilities that improve the accuracy and performance of our recommended models. This session will highlight the forecasting features of Automated ML and how to leverage them.

Jump To:
[00:35] – What is time-series forecasting?
[01:30] – Simplify ML with Automated ML
[02:30] – DriveTime customer scenario
[04:15] – Features & Functionality
[05:20] – Demo

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Really great that you've evolved the orange juice forecast tutorial code with the featurization and generating the actual forecasting. Looking forward to playing .

adamthorne

Is the final API only to predict the future within forecast horizon as shown? If yes, what's the purpose of the model that only "predicts" the knowns. The data within the forecast horizon is nothing but the test dataset used for validation.

Ranbuli

why the video is cut when she is explaining forecast horizons?

bhat

How can we use it for capacity planning for sql servers in on premise environment?

architectingme

There is no module named forecasting_helper

ahsanrazakhan

AI Show: Time Series Forecasting with Automated Machine Learning

AI Show: Time Series Forecasting with Automated Machine Learning

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