Hello! I am working on a project involving the use of CNNs for text classification. I found a very clear example on MathWorks that demonstrates how to transform text using an encoding process and provide it as input to a neural network. One of the initial layers of the network is the word embedding layer, which is responsible for capturing the semantic relationships between words. I'm wondering how this layer can work without directly using the words, but instead working with a numerical representation of them. Thank you very much in advance to anyone who will reply to me. CNN for text classification Are you using ThingSpeak to get your input data? Is there an IoT part of this project? Thank you for your response. I want to clarify that in my project, I am not utilizing ThingSpeak or IoT. Instead, I am working with textual data and the main objective is to classify text strings into different classes. I have referred to the example provided in the link Classify Text Data Using Convolutional Neural Network - MATLAB & Simulink - MathWorks Italia. However, I have a question regarding the role of the wordembedding layer when the input is already represented as numbers due to the encoding process. Since the input is numerical, I am uncertain about how the wordembedding layer contributes to the classification task. Could you help me to understand this? Thank you in advance for your reply ! This forum is intended for IoT and ThingSpeak workflows. If you post your question on MATLAB answers, you will probably get a lot more views and better help. Thank you text classification deep learning convolutional neural network embedding layer
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