January 2018
Beginner to intermediate
284 pages
8h 35m
English
Content preview from Deep Learning Essentials
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Limitations of neural networks
Neural networks are a very potent tool for approximating any non-linear function—a problem that arises very frequently in any pattern recognition or machine learning task. Though they are very powerful in their modeling approach, they have certain limitations, which makes them limited in their abilities for various pattern recognition tasks. A few of those limitations are:
- Fixed sized inputs: A neural network architecture has a fixed number of input layers. As such, it can only take a fixed sized input and output for any task. This is a limiting factor for many pattern recognition tasks. For example, imagine an image captioning task, where the goal of the network is taking an image and generating words as captions. ...
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