DL-Using-Keras | dense layer is a classic fully connected neural network

 by   ChaohuiYu Jupyter Notebook Version: Current License: No License

kandi X-RAY | DL-Using-Keras Summary

kandi X-RAY | DL-Using-Keras Summary

DL-Using-Keras is a Jupyter Notebook library. DL-Using-Keras has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

A dense layer is a classic fully connected neural network layer : each input node is connected to each output node. When we compile our models we use either theano or TensorFlow under the hood for efficient numerical computations. An intuitive explanation from an application standpoint is to note that in machine learning cross-entropy is used to predict class probabilities, and MSE to predict values. For example, to predict if a house will be bough by someone over 40 years or below 40 you use cross-entropy. But if you try to predict the age of the buyer, you use MSE.
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              DL-Using-Keras has a low active ecosystem.
              It has 0 star(s) with 0 fork(s). There are no watchers for this library.
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              It had no major release in the last 6 months.
              DL-Using-Keras has no issues reported. There are no pull requests.
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              The latest version of DL-Using-Keras is current.

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              DL-Using-Keras has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              DL-Using-Keras releases are not available. You will need to build from source code and install.
              Installation instructions, examples and code snippets are available.

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