Ktrain: A Low-code Library For Augmented Machine Learning | Awesome LLM Papers Add your paper to Awesome LLM Papers

Ktrain: A Low-code Library For Augmented Machine Learning

Arun S. Maiya . Arxiv 2020 – 53 citations

[Paper]   Search on Google Scholar   Search on Semantic Scholar
Question Answering

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.

Similar Work