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About Introduction To Deep Learning
This document provides an introduction to deep learning. It defines deep learning as extracting patterns from data using neural networks. Deep learning has become popular due to the availability of big data, powerful hardware like GPUs, improved software techniques, and new models. The basic building block of deep learning is the perceptron, which performs a linear combination of its inputs and passes the result through an activation function to produce an output. Common activation functions include the sigmoid, tanh, and ReLU functions. Activation functions introduce non-linearities that allow neural networks to learn complex patterns from data.
Detailed Information
| Author: | ['xtian_villaruz'] |
|---|---|
| Publication Year: | 2019 |
| Pages: | 151 |
| Language: | English |
| Format: | |
| Price: | FREE |
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