This paper studies the case of big data-based intelligent product potential customer mining internal competition in China Telecom Shanghai Company. Huge amounts of data based on big data table, the use of machine Learning and data analysis technology, using the algorithm of LightGBM, PySpark machine Learning algorithms, Positive Unlabeled Learning algorithm, and predict whether customers buy whole house product, precision marketing into artificial intelligence for the customer, large data capacity, promote the development of intelligent products of the company.

翻译：本文研究中国上海电信公司内大数据智能产品潜在客户采矿内部竞争的案例。 基于大数据表的大量数据,使用机器学习和数据分析技术,使用光速计算法、PySpark机器学习算法、正面无标签学习算法,并预测客户是否购买全套房屋产品、准确推销客户人工智能、大数据能力、促进公司智能产品的开发。