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- W4385957097 abstract "Deep learning is an area that emerged from the capabilities of machine learning and artificial intelligence. In the field of deep learning, various parameters are essential to building an efficient model. These parameters include activation function, loss function, number of layers, number of neurons, and many other essentials. Finding an optimal workable environment by setting all these variables is time-consuming and challenging due to time constraints or projects having sharp deadlines. In this paper, the work is done for the exploration of these parameters that make an environment in which deep learning models work. The experimental results will also be discussed to learn about the best environment that makes text classification optimal in deep learning. These results would help the professionals and researchers to extract a ready-to-work environment for the projects associated with the text classification." @default.
- W4385957097 created "2023-08-18" @default.
- W4385957097 creator A5019619324 @default.
- W4385957097 date "2023-01-01" @default.
- W4385957097 modified "2023-10-17" @default.
- W4385957097 title "Analyzing Optimal Environment for the Text Classification in Deep Learning" @default.
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- W4385957097 doi "https://doi.org/10.1007/978-981-99-2271-0_18" @default.
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