A multi-dimensional and hierarchical comprehensive experimental platform based on Python

In order to meet the needs of curriculum construction for the integration of scientific research and teaching under the background of "new engineering", a multi-dimensional and hierarchical comprehensive experimental platform based on Python was designed. Guided by the professional talent training program, the platform designed multi-dimensional experimental teaching content in three research hotspots: image recognition, machine learning and data analysis. The image recognition experiment starts with text recognition, and then realizes face and license plate recognition through various methods. The machine learning experiment is based on the machine learning algorithm of Python and is applied to corn disease identification. The data analysis experiment uses Python to process Excel data in computing workload and bioinformatics data analysis. Students can choose different experimental projects according to their professional needs and scientific research directions in the experiment, so as to achieve the training goal of teaching students in accordance with their aptitude. The application of the experimental platform in teaching practice shows that students have a deeper understanding of the programming implementation of Python in image recognition, machine learning and data analysis, and enhance their interest in scientific research, thus achieving the goal of integrating scientific research into teaching and improving the quality of undergraduate teaching.