Difference between revisions of "Keras"

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(Created page with "== Keras == <font><i> <br> <br> <u><b>Below are some websites with more information and beginner tutorials</u>:</b></i></font> * [https://www.learndatasci.com/tutorials/pytho...")
 
 
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== Keras ==
 
== Keras ==
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<font><i> Keras is an open-source software library that provides a Python interface for artificial neural networks. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible.
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Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimizers, and a host of tools to make working with image and text data easier to simplify the coding necessary for writing deep neural network code. The code is hosted on GitHub. In addition to standard neural networks, Keras has support for convolutional and recurrent neural networks. It supports other common utility layers like dropout, batch normalization, and pooling. Keras allows users to productize deep models on smartphones (iOS and Android), on the web, or on the Java Virtual Machine. It also allows use of distributed training of deep-learning models on clusters of Graphics processing units (GPU) and tensor processing units (TPU). [https://en.wikipedia.org/wiki/Keras <b>This information was copied from wikipedia.</b>]
 
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<u><b>Below are some websites with more information and beginner tutorials</u>:</b></i></font>
 
<u><b>Below are some websites with more information and beginner tutorials</u>:</b></i></font>
* [https://www.learndatasci.com/tutorials/python-pandas-tutorial-complete-introduction-for-beginners/ Python Pandas Tutorial: A Complete Introduction for Beginners <b>(learndatasci.com)</b>]
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* [https://www.infoworld.com/article/3336192/what-is-keras-the-deep-neural-network-api-explained.html What is Keras? <b>(infoworld.com)</b>]
* [https://towardsdatascience.com/how-to-master-pandas-for-data-science-b8ab0a9b1042 How to Master Pandas for Data Science <b>(towardsdatascience.com)</b>]
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* [https://elitedatascience.com/keras-tutorial-deep-learning-in-python Keras Tutorial: The Ultimate Beginner’s Guide to Deep Learning in Python <b>(elitedatascience.com)</b>]
* [https://www.kaggle.com/learn/pandas Solve Short Hands-on Data Manipulation Challenges <b>(kaggle.com)</b>]
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* [https://www.javatpoint.com/keras Keras Tutorial <b>(javatpoint.com)</b>]
* [https://machinelearningmastery.com/prepare-data-for-machine-learning-in-python-with-pandas/ Prepare Data for Machine Learning in Python with Pandas <b>(machinelearningmastery.com)</b>]
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* [https://keras.io/ Keras: Deep learning for humans <b>(keras.io)</b>]
* [https://towardsdatascience.com/data-manipulation-for-machine-learning-with-pandas-ab23e79ba5de Data Manipulation for Machine Learning with Pandas <b>(towardsdatascience.com)</b>]
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* [https://github.com/keras-team/keras Keras GitHub <b>(github.com)</b>]
  
 
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Latest revision as of 00:26, 8 March 2023

Keras

Keras is an open-source software library that provides a Python interface for artificial neural networks. Designed to enable fast experimentation with deep neural networks, it focuses on being user-friendly, modular, and extensible. Keras contains numerous implementations of commonly used neural-network building blocks such as layers, objectives, activation functions, optimizers, and a host of tools to make working with image and text data easier to simplify the coding necessary for writing deep neural network code. The code is hosted on GitHub. In addition to standard neural networks, Keras has support for convolutional and recurrent neural networks. It supports other common utility layers like dropout, batch normalization, and pooling. Keras allows users to productize deep models on smartphones (iOS and Android), on the web, or on the Java Virtual Machine. It also allows use of distributed training of deep-learning models on clusters of Graphics processing units (GPU) and tensor processing units (TPU). This information was copied from wikipedia.

Below are some websites with more information and beginner tutorials: