Training Mode and Quality View of High-Class Talents

Building a sound system for assessing the training quality of high-class talents with talent introduction as target is helpful effectively analyzing mode in colleges and universities discovering underlying problems weak links, thereby further optimizing current mode, improving level region. However, existing papers generally focus on macroscopic research talents, so this paper attempts to study view under intervention policy. At first, elaborated strategies adjusting policy, gave diagram model, assessed using four selected evaluation indexes, including solid knowledge base, independent ability, rich practical personality career outlook. Then, figure out changes different modes built prediction model based Gated Recurrent Units (GRU) deep neural network, statistics results experiment. last, compared differences