基于Python的多维度、层次化的综合实验平台

Design of Multi-Dimensional and Hierarchical Integrated Experimental Platform Based on Python

为满足“新工科”背景下科研与教学融合的课程建设需求,设计了一套基于Python的多维度、层次化的综合实验平台。平台以专业人才培养方案为导向,在图像识别、机器学习及数据分析3个科研热点方向,设计了多维的实验教学内容。图像识别实验从文字识别入门,进而通过多种方式实现人脸和车牌识别。机器学习实验基于Python的机器学习算法实现,并应用于玉米病害识别。数据分析实验将Python处理Excel数据应用于计算工作量和生物信息数据分析中。学生在实验中可以根据专业需求和科研方向选择不同的实验项目,从而实现因材施教的培养目标。将实验平台应用于教学实践中表明,学生对Python在图像识别、机器学习以及数据分析的编程实现有了更深入的了解,提升了科研兴趣,从而实现将科研融入教学,提高本科生教学质量的目标。

To meet the need of integrating scientific research into teaching of Emerging Engineering Education,a multi-dimensional and hierarchical integrated experimental platform based on Python is designed.Guided by the talent-training plan,hierarchical modules involving image recognition,machine learning and data analysis is designed from scientific research hotspots.Image recognition module starts from character recognition,then face and license plate recognition are realized by several algorithms.In the machine learning module,commonly used machine learning algorithms are studied and corn disease is identified by various methods based on Python.In the data processing and analysis module,Excel data processing experiment based on Python is designed to analyze the data of workload and bioinformatics data.The platform enables students to learn the application of Python in the experiments,and choose different experimental projects according to professional needs and research directions to realize the goal of teaching students in accordance with their aptitude.By applying the experimental platform to teaching practice,it is demonstrated that students have a deeper understanding of Python's programming implementation in image recognition,machine learning,and data analysis and enhanced research interest.And the goal of integrating scientific research into teaching and improving the quality of undergraduate teaching could be achieved.