How this analysis was created: This summary and feature list were written by an AI model that read the project's README and public documentation pages. Each feature links to the documentation it came from; stars, license and language come straight from the GitHub API. The model does not read the source code, and the analysis is refreshed when the project is re-analysed. Learn more on our About page.
Towhee is a framework that is dedicated to making neural data processing pipelines simple and fast.
The main features of towhee-io/towhee are: Machine Learning Frameworks, Data Pipelines, Data Processing and Analysis, Data Science Tooling, Data Science Tools.
Open-source alternatives to towhee-io/towhee include: alteryx/featuretools — Featuretools is an automated feature engineering library and data transformation framework written in Python. It… astrazeneca/rexmex — A general purpose recommender metrics library for fair evaluation. adrotog/pandasgui — A GUI for Pandas DataFrames. albumentations-team/albumentations — Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep… astrazeneca/chemicalx — A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022). benedekrozemberczki/karateclub — Karate Club: An API Oriented Open-source Python Framework for Unsupervised Learning on Graphs (CIKM 2020).
Albumentations is a computer vision image augmentation library designed to increase training data diversity for deep learning models. It provides a toolset for applying geometric and color transformations to images and annotations, including a specialized collection of 3D operations for volumetric data used in medical and scientific imaging. The library functions as an image mask and bounding box transformer, automatically updating masks, bounding boxes, and keypoints when images undergo geometric changes. This ensures that spatial alterations remain synchronized across images and their assoc
Featuretools is an automated feature engineering library and data transformation framework written in Python. It automatically generates machine learning feature vectors from multi-table datasets by applying synthesis patterns to relational and timestamped data. The system functions as a distributed feature synthesis engine, allowing the process of creating feature vectors to scale across multiple cores or clusters to handle large-scale datasets. The library supports the synthesis of multi-table datasets, time series feature generation, and the creation of custom machine learning primitives
A PyTorch and TorchDrug based deep learning library for drug pair scoring. (KDD 2022)
