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GitHub / netik1020 / Concise-iPython-Notebooks-for-Deep-learning

Ipython Notebooks for solving problems like classification, segmentation, generation using latest Deep learning algorithms on different publicly available text and image data-sets.

JSON API: http://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/netik1020%2FConcise-iPython-Notebooks-for-Deep-learning

Stars: 37
Forks: 13
Open issues: 0

License: None
Language: Jupyter Notebook
Size: 9.18 MB
Dependencies parsed at: Pending

Created at: over 6 years ago
Updated at: about 2 years ago
Pushed at: almost 6 years ago
Last synced at: about 2 years ago

Topics: attention-lstm, autoencoder, bi-lstm-crf, deep-neural-networks, deeplearning, image-classification, image-processing, image-segmentation, inception-architecture, intent-classification, keras-neural-networks, semantic-relationship-extraction, snapshot, text-classification, text-generation, text-processing, u-net, unet-keras, word-embeddings

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