Cultivation Path for Innovation Ability of Sci-Tech Talents in the Background of Big Data

Abstract

China mainly relies on higher education to cultivate sci-tech talents. The decision makers and workers of higher education face the important task of cultivating high-quality sci-tech talents that benefits the society. However, the current cultivation system for the innovation ability of high-quality sci-tech talents has some defects, and the practical experience is severely lacking for the cultivation of big data ability of high-quality sci-tech talents. Therefore, this paper explores the cultivation path for innovation ability of sci-tech talents in the background of big data. Firstly, a pre-survey was carried out on the factors affecting the innovation ability of sci-tech talents in the background of big data, an evaluation index system was established for the said ability, and the cultivation path was given for that ability. Next, the gradient boosted decision tree (GBDT) was combined with neural network (NN) into a hybrid approach, which integrates the merits of both methods. The hybrid approach was adopted to analyze and evaluate the factors affecting the innovation ability of sci-tech talents. Then, the authors further explored whether the basic ability, technology ability, and management ability of big data analysis promotes the optimization of the cultivation path for innovation ability of sci-tech talents. Through experiments, the authors obtained the regression analysis results on the innovation ability of sci-tech talents, and put forward suggestions on how to optimize the cultivation path for innovation ability of sci-tech talents.