How to stay updated with the latest advancements in text classification? What are some open-source datasets for text classification?

Evaluate with Argilla¶. Now, we can start the annotation process. Just open the dataset in the Argilla UI and start annotating the records. If the suggestions ... May 20, 2016 ... The basic idea is that semantic vectors (such as the ones provided by Word2Vec) should preserve most of the relevant information about a text ... Jun 9, 2020 ... We provide a guide to help researchers navigate the consequential decisions they need to make before any measure can be produced from the text. The text classification algorithm takes a text string as input and outputs a probability for each of the class labels. Training datasets must be in CSV format. Nov 23, 2022 ... This blog will explore text classification use cases. It also contains an end-to-end example of how to build a text preprocessing pipeline followed by a text ... ... classification result. T This method is a classification enhancement method that can classify patent text alone or enhance the accuracy of various types of ... Custom text classification. Custom named entity recognition (available in containers), $5. Text analytics for health (available in containers), 0M-0M - Included ... Feb 11, 2018 ... I'm able to do text classification and NER using Prodigy, but can I combine the two into a single model which I can load into spacy? Does that make sense? Dec 24, 2022 ... In this post we'll see a demonstration of an NLP-Classification problem with 2 different approaches in python. Jul 17, 2019 ... In this work, we propose to use graph convolutional networks for text classification. We build a single text graph for a corpus based on word co ...