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  2. TensorFlow - Wikipedia

    en.wikipedia.org/wiki/TensorFlow

    TensorFlow includes an “eager execution” mode, which means that operations are evaluated immediately as opposed to being added to a computational graph which is executed later. [35] Code executed eagerly can be examined step-by step-through a debugger, since data is augmented at each line of code rather than later in a computational graph. [35]

  3. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.

  4. Mobile Location Protocol - Wikipedia

    en.wikipedia.org/wiki/Mobile_Location_Protocol

    This protocol has been prepared by Location Interoperability Forum (LIF: Open Mobile Alliance in nowadays) to provide a simple and secure API (Application Programmer’s Interface), but also could be used for other kinds of location servers and entities in the wireless network. The API is based on XML and is defined to be transported in HTTP or ...

  5. Keras - Wikipedia

    en.wikipedia.org/wiki/Keras

    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, models, or metrics that can be used in native workflows in JAX, TensorFlow, or PyTorch — with ...

  6. Service Location Protocol - Wikipedia

    en.wikipedia.org/wiki/Service_Location_Protocol

    The example uses the standard syntax for attributes in SLP, only newlines have been added to improve readability. The definition of a "service:" URL and the allowed attributes for the URL are specified by a service template, a formalized description of the URL syntax and the attributes. Service templates are defined in RFC 2609.

  7. Tensor Processing Unit - Wikipedia

    en.wikipedia.org/wiki/Tensor_Processing_Unit

    Tensor Processing Unit (TPU) is an AI accelerator application-specific integrated circuit (ASIC) developed by Google for neural network machine learning, using Google's own TensorFlow software. [2]

  8. Advanced Vector Extensions - Wikipedia

    en.wikipedia.org/wiki/Advanced_Vector_Extensions

    For example, an SSE instruction using the conventional two-operand form a ← a + b can now use a non-destructive three-operand form c ← a + b, preserving both source operands. Originally, AVX's three-operand format was limited to the instructions with SIMD operands (YMM), and did not include instructions with general purpose registers (e.g ...

  9. Module:Location map/sandbox - Wikipedia

    en.wikipedia.org/wiki/Module:Location_map/sandbox

    This module is subject to page protection.It is a highly visible module in use by a very large number of pages, or is substituted very frequently. Because vandalism or mistakes would affect many pages, and even trivial editing might cause substantial load on the servers, it is protected from editing.