Text Classification


Text classification is the process of assigning tags or categories to text according to its content. It's one of the fundamental tasks in Natural Language Processing (NLP) with broad applications such as sentiment analysis, topic labeling, spam detection, and intent detection.

Overview

Tutorials

PyTorch Transformers Tutorials
A set of annotated Jupyter notebooks, that give user a template to fine-tune transformers model to downstream NLP tasks such as classification, NER etc.
transformers text-classification text-summarization named-entity-recognition
Understanding Convolutional Neural Networks for NLP
More recently we’ve also started to apply CNNs to problems in Natural Language Processing and gotten some interesting results.
convolutional-neural-networks natural-language-processing text-classification tutorial
Practical Text Classification With Python and Keras
You will get a grasp of current advancements of (deep) neural networks and how they can be applied to text.
text-classification keras sentiment-analysis natural-language-processing
Text Classification With Torchtext
This example shows how to train a supervised learning algorithm for classification using one of these TextClassification datasets.
text-classification pytorch torchtext ngrams
Transfer Learning with T5: the Text-To-Text Transfer Transformer
In the paper, we demonstrate how to achieve state-of-the-art results on multiple NLP tasks using a text-to-text transformer pre-trained on a large text ...
transformers t5 question-answering reading-comprehension

Libraries

Transformers - Hugging Face
🤗 Transformers: State-of-the-art Natural Language Processing for TensorFlow 2.0 and PyTorch.
transformers huggingface attention bert
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