Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: Proposed method and security system provide geographical location-based security with varying levels of access. It allows users to select entities to protect, configure geographical locations, geographical boundaries as well as permissions, access level for given geographical locations, geographical boundaries and configure security alerts. It takes decision to grant, deny permission or provide given access level based on user's current geographical location and user's own configuration for that geographical location or boundary and sends out security alerts.

Abstract: Proposed method and security system provide geographical location-based security with varying levels of access, allows users to select entities to protect, configure geographical locations, geographical boundaries as well as permissions, access level for given geographical locations, geographical boundaries and configure security alerts. It takes decision to grant, deny permission or provide coven access level based on user's current geographical location and user's own configuration for that geographical location or boundary and sends out security alerts.