5 Neural Networks
Warning🚧 Under Construction
This chapter is currently being developed. Check back soon for updates!
5.1 Introduction to Neural Networks
NoteComing Soon
- Perceptrons and activation functions
- Feedforward networks
- Backpropagation
5.2 Flux.jl Basics
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- Installing Flux.jl
- Building your first neural network
- Training loops
5.3 Deep Learning Architectures
5.3.1 Convolutional Neural Networks (CNNs)
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- Convolution operations
- Pooling layers
- Image classification for geoscience
5.3.2 Recurrent Neural Networks (RNNs)
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- LSTM and GRU cells
- Time series prediction
- Sequence modeling for seismic data
5.3.3 Autoencoders
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- Encoder-decoder architecture
- Variational autoencoders
- Dimensionality reduction
5.4 Training Best Practices
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- Data preprocessing and normalization
- Batch training
- Learning rate scheduling
- Regularization techniques
5.5 GPU Computing with CUDA.jl
NoteComing Soon
- GPU setup
- Moving data to GPU
- Performance optimization