What are activation functions in neural networks?

Mar 29, 2024 ... Text data augmentation and pre-trained Language Model for enhancing text classification of low-resource languages Abstract. This article offers an empirical exploration on the use of character-level convolutional networks (ConvNets) for text classification. We constructed ... Dec 24, 2022 ... In this post we'll see a demonstration of an NLP-Classification problem with 2 different approaches in python. Oct 28, 2024 ... A comprehensive guide to implementing machine learning NLP text classification algorithms and models on real-world datasets. Text classification is a Machine Learning approach for automatically categorizing open-ended text into a number of predetermined categories. Text classifiers ... This paper compares the performance of ten such approaches (five lexicon-based, five machine learning algorithms) across 41 social media datasets. The AutoKeras TextClassifier is quite flexible for the data format. For the text, the input data should be one-dimensional. Apr 24, 2025 ... Let's try to demonstrate this by providing an example of text classification. Prompt: Classify the text into neutral, negative or positive. Text ... Apr 3, 2025 ... Text classification is a key natural language processing task widely used in areas such as news classification, sentiment analysis, topic ... Measuring and Mitigating Unintended Bias in Text Classification · Abstract · Research Areas. Natural Language Processing · Responsible AI. Meet the teams ...