August 2024
Intermediate to advanced
374 pages
8h 44m
English
Content preview from Machine Learning in ElixirBecome an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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Introducing Recurrent Neural Networks
You might be curious why basic feed-forward networks alone aren’t ideal for processing sequences. The problem is that basic feed-forward networks don’t have any way to account for temporal dependencies.
Temporal dependencies are simply dependencies on time. When dealing with sequences, it’s common to refer to the entries in the sequence as individual timesteps, regardless of whether entries map to actual timesteps. A temporal dependency means that events that happen in the future are dependent on what has happened in the past, or what is currently happening. If you think about this in the context of natural language, it should make sense.
In a sequence of words from natural language, order matters. The ...
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