Preparing data for machine learning processing

A computer-implemented method, comprising:

• preparing data for processing by a first machine learning model by at least embedding a second portion of the data including a textual data, the textual data being embedded by at least applying a second machine learning model trained to embed the textual data;
• preparing the data for processing by the first machine learning model, the data being prepared by at least encoding a first portion of the data including a spatial data, the spatial data including a first spatial coordinate including one or more values identifying a geographical location, wherein the encoding of the first portion of the data includes mapping, to a first cell in a grid system, the first spatial coordinate such that the first spatial coordinate is represented by a first identifier of the first cell instead of the one or more values;
• executing, based on the embedded textual data, a plurality of machine learning trials, each of the plurality of machine learning trials being executed by at least retrieving, from a cache, the embedded textual data, wherein each of the plurality of machine learning trials includes a different machine learning model and/or a different set of trial parameters, and wherein the first machine learning model is selected based at least on a result of the plurality of machine learning models;
• and
• applying, to the prepared data, the first machine learning model.

A non-transitory computer readable medium storing instructions, which when executed by at least one data processor, result in operations comprising:

• preparing data for processing by a first machine learning model by at least embedding a second portion of the data including a textual data, the textual data being embedded by at least applying a second machine learning model trained to embed the textual data;
• preparing the data for processing by the first machine learning model, the data being prepared by at least encoding a first portion of the data including a spatial data, the spatial data including a first spatial coordinate including one or more values identifying a geographical location, wherein the encoding of the first portion of the data includes mapping, to a first cell in a grid system, the first spatial coordinate such that the first spatial coordinate is represented by a first identifier of the first cell instead of the one or more values;
• executing, based on the embedded textual data, a plurality of machine learning trials, each of the plurality of machine learning trials being executed by at least retrieving, from a cache, the embedded textual data, wherein each of the plurality of machine learning trials includes a different machine learning model and/or a different set of trial parameters, and wherein the first machine learning model is selected based at least on a result of the plurality of machine learning models;
• and
• applying, to the prepared data, the first machine learning model.