Journal
KNOWLEDGE-BASED SYSTEMS
Volume 178, Issue -, Pages 48-50Publisher
ELSEVIER SCIENCE BV
DOI: 10.1016/j.knosys.2019.04.013
Keywords
Deep learning; Weka
Categories
Funding
- Marsden Fund of New Zealand - Millennium Institute for Foundational Research on Data [15-UOW-094]
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Deep learning is a branch of machine learning that generates multi-layered representations of data, commonly using artificial neural networks, and has improved the state-of-the-art in various machine learning tasks (e.g., image classification, object detection, speech recognition, and document classification). However, most popular deep learning frameworks such as TensorFlow and PyTorch require users to write code to apply deep learning. We present WekaDeeplearning4j, a Weka package that makes deep learning accessible through a graphical user interface (GUI). The package uses Deeplearning4j as its backend, provides GPU support, and enables GUI-based training of deep neural networks such as convolutional and recurrent neural networks. It also provides pre-processing functionality for image and text data. (C) 2019 Elsevier B.V. All rights reserved.
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