With Artificial Neural Networks (ANN), let's try to simulate typical brain activities such as image perception, pattern recognition, language understanding, sense-motor coordination, and so on. ANN models are composed of a system of nodes, equivalent to neurons of a human brain, which are interconnected by weighted links, equivalent to synapses between neurons. The output of the network is modified iteratively from link weights to convergence.
This final chapter presents ANN applications from different use cases and how neural networks can be used in the AI world. We will see some use cases and their implementation in R. You can adapt the same set of programs for other real work scenarios.
The following topics will be covered:
- TensorFlow integration with R
- Keras integration with R
- Handwritten digit recognition using MNIST...
