Emotion estimation is a field that has been studied for a long time, and several approaches using machine learning models exist. This article presents BlendFER-Lite, an LSTM model that uses ...
Regularizing and Optimizing LSTM Language Models An Analysis of Neural Language Modeling at Multiple Scales This code was originally forked from the PyTorch word level language modeling example. The ...
Time-series data in manufacturing (temperature, pressure, vibration, current...) is tricky. Data preprocessing, windowing, normalization, the format to pass to the model... "I'll visualize that data ...
Example models are in src/models/, the data generators used for training are in src/helpers/image_functions.py. To get the accuracy scores and the confusion matrix of ...
Bacteriophages are gaining increasing interest as antimicrobial tools, largely due to the emergence of multi-antibiotic–resistant bacteria. Although their huge diversity and virulence make them ...
An LSTM autoencoder combines encoder-decoder architecture to compress and reconstruct data effectively. Long Short Term Memory networks excel in learning dependencies in sequential data. The article ...
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