Deep Learning Math Workbook is a practical, exercise-based guide to understanding the mathematics behind neural networks, written by Prof. Tom Yeh, creator of the global AI by Hand movement. Rather than relying solely on formulas or code, this workbook invites you to compute, visualize, and think through every step, like solving crossword puzzles that train your mathematical intuition.
With the help of 300 original AI by Hand exercises, you’ll progress methodically from the basics to advanced deep learning concepts. Each chapter, Dot Product, Matrix Multiplication, Linear Layer, Activation, Artificial Neuron, Batch, Connection, Hidden Layer, Deep, Wide, Softmax, and Gradient, builds toward understanding how modern neural networks actually work.
Even though most AI books skip the arithmetic, this workbook makes every computation explicit and intuitive. You’ll see and feel how each operation transforms data, helping you develop deep intuition for how learning happens inside the model.
This is more than a math book, it’s an interactive learning experience that rewards persistence.

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Spis treści

Deep Learning Math Workbook. 300 puzzles to build your mathematical foundation for deep learning eBook -- spis treści

• 1. Dot Product
• 2. Matrix Multiplication
• 3. Linear Layer
• 4. Activation
• 5. Artificial Neuron
• 6. Batch
• 7. Connection
• 8. Hidden Layer
• 9. Deep
• 10. Wide
• 11. Softmax
• 12. Gradient