We present ktrain, a low-code Python library that makes machine learning more accessible and easier to apply. As a wrapper to TensorFlow and many other libraries (e.g., transformers, scikit-learn, stellargraph), it is designed to make sophisticated, state-of-the-art machine learning models simple to build, train, inspect, and apply by both beginners and experienced practitioners. Featuring modules that support text data (e.g., text classification, sequence tagging, open-domain question-answering), vision data (e.g., image classification), graph data (e.g., node classification, link prediction), and tabular data, ktrain presents a simple unified interface enabling one to quickly solve a wide range of tasks in as little as three or four "commands" or lines of code.
翻译:我们展示了Ktrain, 这是一种低码的Python 图书馆, 使机器学习更便于使用和更容易应用。 作为TensorFlow和许多其他图书馆( 如变压器、 缩略图- learn、 星光图等)的包装器, 设计它的目的是让尖端的、 最先进的机器学习模型简单地为初学者和有经验的实践者建立、 培训、 检查和应用。 使用支持文本数据( 如文本分类、 序列标记、 开放式问答)、 视觉数据( 如图像分类)、 图表数据( 如节点分类、 链接预测) 和表格数据, ktrain 提供了一个简单的统一界面, 使一个人能够快速解决三到四条“ 命令” 或代码线上的广泛任务 。