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2. Keras - Wikipedia

   en.wikipedia.org/wiki/Keras

   Keras is an open-source library that provides a Python interface for artificial neural networks.Keras was first independent software, then integrated into the TensorFlow library, and later supporting more.

3. TensorFlow - Wikipedia

   en.wikipedia.org/wiki/TensorFlow

   TensorFlow also offers a variety of libraries and extensions to advance and extend the models and methods used. [67] For example, TensorFlow Recommenders and TensorFlow Graphics are libraries for their respective functionalities in recommendation systems and graphics, TensorFlow Federated provides a framework for decentralized data, and ...

4. Comparison of deep learning software - Wikipedia

   en.wikipedia.org/wiki/Comparison_of_deep...

   Can use Theano, Tensorflow or PlaidML as backends Yes No Yes Yes [20] Yes Yes No [21] Yes [22] Yes MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24 ...

5. Deep learning - Wikipedia

   en.wikipedia.org/wiki/Deep_learning

   Deep learning is a subset of machine learning that focuses on utilizing neural networks to perform tasks such as classification, regression, and representation learning.The field takes inspiration from biological neuroscience and is centered around stacking artificial neurons into layers and "training" them to process data.

6. Tensor Processing Unit - Wikipedia

   en.wikipedia.org/wiki/Tensor_Processing_Unit

   The tensor processing unit was announced in May 2016 at Google I/O, when the company said that the TPU had already been used inside their data centers for over a year. [ 5 ] [ 4 ] Google's 2017 paper describing its creation cites previous systolic matrix multipliers of similar architecture built in the 1990s. [ 8 ]

7. Remote job entry - Wikipedia

   en.wikipedia.org/wiki/Remote_Job_Entry

   Remote job entry, or Remote Batch, is the procedure for sending requests for non-interactive data processing tasks to mainframe computers from remote workstations, and by extension the process of receiving the output from such jobs at a remote workstation.