Table of Contents
- A Quick Refresher
- Building our first Neural Network Together
- Decision Tress and Random Forests
- Face and Motion Detection
- Training CNNs using ConvNetSharp
- Training Autoencoders Using RNNSharp
- Replacing Back Propagation with PSO
- Function Optimizations; How and Why
- Finding Optimal Parameters
- Object Detection with TensorFlowSharp
- Time Series Prediction and LSTM Using CNTK
- GRUs Compared to LSTMs, RNNs, and Feedforward Networks
- Appendix A- Activation Function Timings
- Appendix B- Function Optimization Reference

