We introduce MOSAIC, a Python program for machine learning models. Our framework is developed with in mind accelerating machine learning studies through making implementing and testing arbitrary network architectures and data sets simpler, faster and less error-prone. MOSAIC features a full execution pipeline, from declaring the models, data and related hyperparameters within a simple configuration file, to the generation of ready-to-interpret figures and performance metrics. It also includes an advanced run management, stores the results within a database, and incorporates several run monitoring options. Through all these functionalities, the framework should provide a useful tool for researchers, engineers, and general practitioners of machine learning.
翻译:我们引入了MOSAIC,这是一个用于机器学习模型的Python方案,我们的框架是在考虑加速机器学习研究的同时制定的,其方法是通过实施和测试任意的网络架构和数据集更加简单、快捷和不易出错。 MOSAIC有一个完整的执行管道,从在简单配置文档中宣布模型、数据和相关超参数,到生成随时可解释的数字和性能衡量标准,还包括先进的运行管理,将结果储存在一个数据库中,并包含若干运行的监测选项。 通过所有这些功能,该框架应该为研究人员、工程师和机器学习的一般实践者提供有用的工具。