Sentence examples for Learning complexity from inspiring English sources

However, it is subjected to the model selection and learning complexity O K * N3), especially for a massive data set (N is the size of training dataset, and K is the number of search).

A number of fundamental issues are tackled including specificity of information granules vis-a-vis learning complexity in the neural networks along with their generalization features.

We do not think Feltovich et al. intended their framework to necessarily apply to a biology classroom; however, we attempted to show how it can be used to guide research on how students learn complexity and ultimately guide instruction that assists students in learning about complex biological systems.

But small steps, like focusing on a single understudied dimension or applying what is known from well-studied dimensions to similar dimensions, can lead to generalizations that will advance our knowledge about how students know and learn complexity.

This essay seeks to promote greater discussion around the idea of what makes biological systems complex and how we can improve students' learning about complexity.

The goal of this commentary is to present a framework for a language of complexity that may aid instructors in this endeavor, as well as education researchers who seek to understand student learning about complexity.

This requires networked thinking on the part of the learner and increases the learning goals' complexity dramatically.

To simplify learning space complexity, we propose, from the standpoint of learning control, that robot motions be classified according to their similarities.

So, if the students' are supposed to be able to be a part of their own learning the complexity in the task should not be too high.

After learning, the complexity of the extracted features increased along the hierarchy, from edge detectors in the first layer to object prototypes in the last layer.

The feedback shows that the game is a valuable tool in environmental education initiating learning the complexity of feedbacks in land use and resources appropriation.