Long Short Term Memory Networks - PowerPoint PPT Presentation
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Long Short Term Memory Networks
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Long short-term memory networks, or LSTMs, are employed in deep learning. Various recurrent neural networks are capable of learning long-term dependencies, especially in tasks involving sequencing predictions. For more information, Pls visit the 1stepgrow website. – PowerPoint PPT presentation
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Title: Long Short Term Memory Networks
1
Long Short Term Memory Networks (LSTMs) In Deep
Learning
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and-artificial-intelligence-course/
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Table Of Content
- What Is a LSTMs Algorithm?
- Why Is the LSTMs Algorithm Important?
- How Does LSTMs Algorithm Work?
- Applications Of LSTMs Algorithm
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What Is a LSTMs Algorithm?
Long short-term memory networks are employed in
deep learning. Recurrent neural networks can
learn long-term dependencies, especially in
sequencing prediction tasks.
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and-artificial-intelligence-course/
4
Why Is the LSTMs Algorithm Important?
Because it enables the learning of even more
parameters, the Long short-term memory cell
increases long-term memory even more
efficiently. As a result, it is the most
effective for predicting, particularly when your
data show a longer-term trend.
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5
How Does LSTMs Algorithm Work?
A series of gates used by Long short - term
memory regulate how data in a series enters, is
saved in, and leaves the network. A common Long
short - term memory has three gates an outputs
gate, an input gate, and a forget gate. Every
one of these gates is a separate neural network
and may be considered to function as a filter.
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Applications Of LSTMs Algorithm
Due to their ability to understand long- term
connections between data clock cycles, Long
short-term memory networks are frequently used
to understand, analyze, and categorize sequence
information. Sentiment analysis, language
processing, voice recognition, and video
analysis are examples of common Long short-term
memory network applications. https//1stepgrow.co
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ligence-course/
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THANK YOU!
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