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Datasets for training and testing.
We used a few different speech datasets for training and testing.
In the image retrieval process, using different datasets for training the codebook will produce different results.
The lack of availability of datasets for training and validation is often a major problem.
The main challenge of CNN-based stereo matching algorithms is that they require large datasets for training.
In this section, we first describe the generation of the datasets for training and testing and the setup of the training parameters of the deep networks.
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"This is our main dataset for training our own algorithms.
For small training dataset, it is beneficial because we could have sufficient training dataset for training an NN.
The conversations thus obtained were labeled to create a 'labeled dataset' for training and testing purposes.
Moreover, classifiers usually have to rely on a large-scale dataset for training.
The benefit of using Naïve Bayes on text classification is that it needs small dataset for training.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com