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- Introduction
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Classroom Contents
Neural Networks and Multi-Layer Perceptrons - Understanding the Fundamentals
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- 1 - Introduction
- 2 - Perceptrons and Artificial Neurons
- 3 - Activation Functions
- 4 - Multi-Layer Perceptrons
- 5 - Universal Function Approximators
- 6 - Modeling Inputs for a Neural Networks
- 7 - Outputs for Classification and Regression Tasks
- 8 - Vectorization
- 9 - Tensors and GPUs
- 10 - Processing data in Batches
- 11 - Summary Map
- 12 - Conclusion
