DL-Using-Keras | dense layer is a classic fully connected neural network
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.
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.
It had no major release in the last 6 months.
DL-Using-Keras has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of DL-Using-Keras is current.
Quality
DL-Using-Keras has no bugs reported.
Security
DL-Using-Keras has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
License
DL-Using-Keras does not have a standard license declared.
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Without a license, all rights are reserved, and you cannot use the library in your applications.
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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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DL-Using-Keras Key Features
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DL-Using-Keras Examples and Code Snippets
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Install DL-Using-Keras
You can download it from GitHub.
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