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AIFH: Introduction to the Math of Neural Networks

Please note: This material is for an upcoming book.

This book has the following chapters:

  • Chapter 1. Activation
  • Chapter 2. Error Calculation
  • Chapter 3. Differentiation
  • Chapter 4. Numeric Differentiation
  • Chapter 5. Symbolic Differentation
  • Chapter 6. Backpropagation
  • Chapter 7. Enhancements to Backpropagation
  • Chapter 8. Linear Algebra
  • Chapter 9. Integration
  • Chapter 10. Probability
  • Chapter 11. Statistics
  • Chapter 12. Pseudo Random Number Generation
  • Chapter 13. Self-Organizing Maps
  • Chapter 14. Preprocessing

The following language ports have been completed for this book. See the individual README files inside of each chapter for language specific instructions. If you find a bug, or improve an example, please consider pushing a change via GitHub.

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