【GAMI Open Course】Introduction to Data Analysis and Machine Learning in Production

In the field of manufacturing, there is a diverse array of data, and the quantity is substantial. From raw material procurement, inventory management, production process monitoring, to product quality testing and post-sales analysis, each stage generates a large volume of data. Effectively harnessing this data can significantly enhance a company's production efficiency and product quality, thereby strengthening its competitiveness. In a one-day course, we will focus on how to handle this data and utilize machine learning techniques to achieve data intelligence. By the end of the course, participants should have a basic proficiency in progressing from data collection to model deployment and be able to identify and assess the potential applications of machine learning in their own work environments.

在生产领域，数据的种类多样且数量巨大。从原材料采购、库存管理、生产过程监控、到产品质量检测和销售后分析，每一个环节都产生着大量数据。有效地利用这些数据可以显著提高企业的生产效率和产品质量，进而增强企业竞争力。在一天的课程中，我们将重点介绍如何处理这些数据并利用机器学习技术实现数据智能。课程结束时，学员应具备从数据收集到模型部署的基本能力，并能够识别和评估机器学习在自己工作环境中的潜在应用。

Outline 大纲

• Introduction
• Basic concepts
• Machine Learning Algorithms I
• Machine Learning Algorithms II
• CRISP-DM Models
• LLM and ChatGPT
• Application Cases
• Review and discussion

• 引言
• 基本概念
• 机器学习算法I
• 机器学习算法II
• CRISP-DM模型
• LLM和ChatGPT
• 应用案例
• 回顾与讨论