MachineLearningJournalClub/LearningNLP
Some Tutorials & in depth analysis of NLP's algorithms with an ethical flavour
This collection of tutorials helps you understand and apply natural language processing (NLP) techniques, from basic sentiment analysis to identifying bias in text. You'll start with raw text data and learn how to extract insights like sentiment scores, political leanings, or underlying topics. This resource is designed for data scientists, machine learning practitioners, and researchers looking to deepen their practical knowledge of NLP, including its ethical considerations.
No commits in the last 6 months.
Use this if you want to learn practical NLP applications, understand how to interpret model predictions, and explore ethical concerns like bias and fairness in text analysis.
Not ideal if you are looking for a plug-and-play tool for immediate deployment without needing to understand the underlying NLP concepts.
Stars
14
Forks
5
Language
Jupyter Notebook
License
—
Category
Last pushed
Oct 07, 2021
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/MachineLearningJournalClub/LearningNLP"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
RingBDStack/SocialED
A python library for social event detection
rguthrie3/DeepLearningForNLPInPytorch
An IPython Notebook tutorial on deep learning for natural language processing, including...
mesolitica/NLP-Models-Tensorflow
Gathers machine learning and Tensorflow deep learning models for NLP problems, 1.13 < Tensorflow < 2.0
DSKSD/DeepNLP-models-Pytorch
Pytorch implementations of various Deep NLP models in cs-224n(Stanford Univ)
mannefedov/compling_nlp_hse_course
Материалы курса по компьютерной лингвистике Школы Лингвистики НИУ ВШЭ