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ktrain: A Low-Code Library for Augmented Machine Learning

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arxiv 2004.10703 v5 pith:XLO456NE submitted 2020-04-19 cs.LG cs.CLcs.CVcs.SI

classification cs.LGcs.CLcs.CVcs.SI
keywords dataclassificationktrainlearningmachineapplylibrarylow-code
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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