Usually used as a simple example for how deep learning neural networks work, a feed-forward neural network is the most basic, “vanilla” general kind of neural network. In this episode of the AI Today podcast hosts Kathleen Walch and Ron Schmelzer define the term Feed-Forward Neural Network, explain how these terms relate to AI and why it’s important to know about them.
Want to dive deeper into an understanding of artificial intelligence, machine learning, or big data concepts? Want to learn how to apply AI and data using hands-on approaches and the latest technologies? Check out these hand-selected books in our Suggested Reading List that can help you expand your knowledge or put your knowledge to use.
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- AI Glossary
- Glossary Series: Training Data, Epoch, Batch, Learning Curve
- Glossary Series: (Artificial) Neural Networks, Node (Neuron), Layer
- Glossary Series: Bias, Weight, Activation Function, Convergence, ReLU
- Glossary Series: Perceptron
- Glossary Series: Hidden Layer, Deep Learning
- Glossary Series: Loss Function, Cost Function & Gradient Descent
- Glossary Series: Backpropagation, Learning Rate, Optimizer