# ktrain: A Low-Code Library for Augmented Machine Learning

arXiv: https://arxiv.org/abs/2004.10703 · HTML: https://mlsanity.com/paper/2004.10703/

## Key facts

- Cited by 23 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 19 Apr 2020.

## Built on by (most cited first, 23 of 23)

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- [CausalNLP: A Practical Toolkit for Causal Inference with Text](https://mlsanity.com/paper/2106.08043/) (2021)
- [Detecting potentially harmful and protective suicide-related content on twitter: A machine learning approach](https://mlsanity.com/paper/2112.04796/) (2021)
- [Characterizing Information Seeking Events in Health-Related Social Discourse](https://mlsanity.com/paper/2308.09156/) (2023)
- [ArCovidVac: Analyzing Arabic Tweets About COVID-19 Vaccination](https://mlsanity.com/paper/2201.06496/) (2022)
- [LEIA: Linguistic Embeddings for the Identification of Affect](https://mlsanity.com/paper/2304.10973/) (2023)
- [The Potential of AutoML for Recommender Systems](https://mlsanity.com/paper/2402.04453/) (2024)
- [Navigating the Kaleidoscope of COVID-19 Misinformation Using Deep Learning](https://mlsanity.com/paper/2110.15703/) (2021)
- [AI Generated Text Detection Using Instruction Fine-tuned Large Language and Transformer-Based Models](https://mlsanity.com/paper/2507.05157/) (2025)
- [NLP-CUET@DravidianLangTech-EACL2021: Investigating Visual and Textual Features to Identify Trolls from Multimodal Social Media Memes](https://mlsanity.com/paper/2103.00466/) (2021)
- [Probabilistic Impact Score Generation using Ktrain-BERT to Identify Hate Words from Twitter Discussions](https://mlsanity.com/paper/2111.12939/) (2021)
- [SSS at SemEval-2023 Task 10: Explainable Detection of Online Sexism using Majority Voted Fine-Tuned Transformers](https://mlsanity.com/paper/2304.03518/) (2023)
- [STF: Sentence Transformer Fine-Tuning For Topic Categorization With Limited Data](https://mlsanity.com/paper/2407.03253/) (2024)
- [Secondary Use of Clinical Problem List Entries for Neural Network-Based Disease Code Assignment](https://mlsanity.com/paper/2112.13756/) (2021)
- [An approach to standardize, automate omni-channel and AI transactional digital service creation](https://mlsanity.com/paper/2211.03543/) (2022)
- [Improving Cancer Hallmark Classification with BERT-based Deep Learning Approach](https://mlsanity.com/paper/2305.03501/) (2023)
- [Speech Wikimedia: A 77 Language Multilingual Speech Dataset](https://mlsanity.com/paper/2308.15710/) (2023)
- [An Information Retrieval and Extraction Tool for Covid-19 Related Papers](https://mlsanity.com/paper/2401.16430/) (2024)

## Abstract (arXiv)

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.