Big Data and Higher Vocational and Technical Education: Green Food and Its Industry Orientation

This paper aims to focus on a series of issues related to green food and its industry orientation through big data and higher vocational and technical education technologies. The method consists of three steps the first step is to lock in the research objectives, namely: a series of problems in green food and its industry orientation; the second step is to distinguish three types of problems, namely: the first category is a large probability event, the predictable problem is directly solved by machine learning; the second category is a small probability event, which relies solely on machine automatic processing or batch processing can't solve problems, using a variety of human-computer interaction methods to deal with; the third category is cases and very special exceptions, usually only rely on the corresponding human experts to find the ways, and then, through the knowledge acquisition path to develop a dedicated artificial intelligence system. The third step is to incorporate them into the actual classroom teaching practice, or find the special daily life circle, it can be artificially set, even virtual, and tested in various application environments. The result is: through the teachers and students to continue to explore a series of issues related to green food and its industry forming the characteristics of big data and higher vocational and technical education technology. The significance is that is, a series of results of the research of the smart system can be directly used to study a series of problems focusing on green food and its industrial orientation.