jdvala/lazytext
LazyText is inspired by the idea of lazypredict, a library which helps build lot of basic models without much code. LazyText is for text what lazypredict is for numeric data.
This tool helps data professionals quickly compare many different machine learning models for classifying text data. You input your text and its associated categories, and it automatically tests numerous models, showing you which ones perform best. This is ideal for data scientists or machine learning engineers who need to efficiently choose the optimal model for text classification tasks.
No commits in the last 6 months. Available on PyPI.
Use this if you need to rapidly evaluate multiple machine learning models to find the best fit for your text classification problem without writing extensive code for each model.
Not ideal if you need deep, custom control over individual model training parameters, or if your primary goal is not comparing multiple models for text classification.
Stars
18
Forks
1
Language
Python
License
MIT
Category
Last pushed
Feb 19, 2022
Commits (30d)
0
Dependencies
3
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/nlp/jdvala/lazytext"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
angelosalatino/cso-classifier
Python library that classifies content from scientific papers with the topics of the Computer...
newsgac/platform
Platform for machine learning experiments developed in the project NEWSGAC
giuseppebonaccorso/Reuters-21578-Classification
Text classification with Reuters-21578 datasets using Gensim Word2Vec and Keras LSTM
aqibsaeed/Research-Paper-Categorization
Research paper classification using machine learning and NLP
tblock/10kGNAD
Ten Thousand German News Articles Dataset for Topic Classification