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A binary-to-text encoding is encoding of data in plain text.More precisely, it is an encoding of binary data in a sequence of printable characters.These encodings are necessary for transmission of data when the communication channel does not allow binary data (such as email or NNTP) or is not 8-bit clean.
An autoencoder is a type of artificial neural network used to learn efficient codings of unlabeled data (unsupervised learning).An autoencoder learns two functions: an encoding function that transforms the input data, and a decoding function that recreates the input data from the encoded representation.
In that way, the same parameters are reused for multiple data points, which can result in massive memory savings. The first neural network takes as input the data points themselves, and outputs parameters for the variational distribution. As it maps from a known input space to the low-dimensional latent space, it is called the encoder.
CBOR encoded data is seen as a stream of data items. Each data item consists of a header byte containing a 3-bit type and 5-bit short count. This is followed by an optional extended count (if the short count is in the range 24–27), and an optional payload. For types 0, 1, and 7, there is no payload; the count is the value. For types 2 (byte ...
OpenAI claims that the combination of different training data used in its development has led to improved recognition of accents, background noise and jargon compared to previous approaches. [3] Whisper is a weakly-supervised deep learning acoustic model, made using an encoder-decoder transformer architecture. [1]
^ Omitted XML elements are commonly decoded by XML data binding tools as NULLs. Shown here is another possible encoding; XML schema does not define an encoding for this datatype. ^ The RFC CSV specification only deals with delimiters, newlines, and quote characters; it does not directly deal with serializing programming data structures.
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