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  2. Model of computation - Wikipedia

    en.wikipedia.org/wiki/Model_of_computation

    A model describes how units of computations, memories, and communications are organized. [1] The computational complexity of an algorithm can be measured given a model of computation. Using a model allows studying the performance of algorithms independently of the variations that are specific to particular implementations and specific technology.

  3. Seq2seq - Wikipedia

    en.wikipedia.org/wiki/Seq2seq

    Shannon's diagram of a general communications system, showing the process by which a message sent becomes the message received (possibly corrupted by noise). seq2seq is an approach to machine translation (or more generally, sequence transduction) with roots in information theory, where communication is understood as an encode-transmit-decode process, and machine translation can be studied as a ...

  4. 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. "Keras 3 is a full rewrite of Keras [and can be used] as a low-level cross-framework language to develop custom components such as layers ...

  5. Comparison of deep learning software - Wikipedia

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

    Self-contained DNN Model Pre-processing and Post-processing Run-time configuration for tuning & calibration DNN model interconnect Common platform TensorFlow, Keras, Caffe, Torch: Algorithm training No No / Separate files in most formats No No No Yes ONNX: Algorithm training Yes No / Separate files in most formats No No No Yes

  6. Long short-term memory - Wikipedia

    en.wikipedia.org/wiki/Long_short-term_memory

    In theory, classic RNNs can keep track of arbitrary long-term dependencies in the input sequences. The problem with classic RNNs is computational (or practical) in nature: when training a classic RNN using back-propagation, the long-term gradients which are back-propagated can "vanish", meaning they can tend to zero due to very small numbers creeping into the computations, causing the model to ...

  7. Sequential algorithm - Wikipedia

    en.wikipedia.org/wiki/Sequential_algorithm

    In computer science, a sequential algorithm or serial algorithm is an algorithm that is executed sequentially – once through, from start to finish, ...

  8. One-way interview - Wikipedia

    en.wikipedia.org/wiki/One-way_interview

    The interviewer creates questions in text or audio format, records their interview questions, or prepares sample scenarios/coding challenges for the online interview. [4] The interviewer invites candidates for the online interview via email. The candidate opens the link to the online interview in a web browser or mobile application and then ...

  9. Sequential estimation - Wikipedia

    en.wikipedia.org/wiki/Sequential_estimation

    Sequential estimation is the core of many well known applications, such as the Viterbi decoder, convolutional codes, video compression or target tracking. Due to its state space representation, which is in most cases motivated by physical laws of motion, there is a direct link to control applications, which led to the use of the Kalman filter ...

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