Using the Keras API together with TensorFlow gives you the flexibility you need to develop *anything* -- it provides you with a spectrum of features from the the highest level of abstraction to the lowest level.
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Keras is one of the most adopted frameworks among deep learning researchers -- because it makes it possible to develop advanced architectures efficiently (ease of use) and get them working in few iterations (good defaults)pic.twitter.com/HYTlzH8Hzt
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I have been using Keras since 1.0 I have just one request. TensorRT is optimized for pure TF but not for tf.keras. Can you talk to the Nvidia guys, if possible, for any reason?
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Keras with TF backend is my favorite. I am a data scientist and use Keras regularly. It helps me put more time for strategic thinking/analysis rather than coding/models. Thanks!
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the n00b friendliness of keras, jupyter notebooks and your excellent book makes development a lot of fun! thank you!
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What did you use to generate this data btw?
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Keras is amazing. Just need a Brain().doStuff() api now
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DL4J is best left out of this list in my opinion (I used it extensively for a year, so I know it better than most, I started there because Java). I see it as a growing collection of poorly organized code. As such it does not come close to the frameworks on this list.
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I'm sorry you see it like that. I would love some direct feedback if you have any for us. With the eclipse foundation migration we are hoping to make the experience better for folks.
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Absolutely true. And
@RapidMiner ‘s Keras extension makes it fast and simple.
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This depends on what you are doing. For text classification and
#word2vec word embedding into vectors according to the evaluation results#FastText is the state of the art at this time https://arxiv.org/pdf/1712.09405.pdf …Thanks. Twitter will use this to make your timeline better. UndoUndo
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