Basic FFNN + Trainer

v0.1

• clean and stable basic FFNN with well-separated component class structure
• includes most common activation functions
• provides derivatives d/dx, d²/dx², d/dv, d²/dv/dx, d³/dv/dx²
• is reasonably performance optimized
• handles least-squares-fitting (training) against target data with minimal hassle for the user
• allows data split in training/validation/testing and early stopping technique