ktrain: A Low-Code Library for Augmented Machine Learning

TL;DR

ktrain is a user-friendly low-code Python library that simplifies building, training, and applying advanced machine learning models across various data types, making ML accessible to both beginners and experts.

Contribution

It introduces a unified, low-code interface for diverse ML tasks, integrating multiple libraries to streamline model development and deployment.

Findings

Supports text, vision, graph, and tabular data tasks

Enables quick model development with minimal code

Integrates multiple ML libraries for versatility

Abstract

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.