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Prologue -- Introduction -- How they work -- Easy for me, hard for you -- A simple predicting machine -- Classifying is not very different from predicting -- Training a simple classifier -- Sometimes one classifier is not enough -- Neurons, nature's computing machines -- Following signals through a neural network -- Matrix multiplication is useful...honest! -- A three layer example with matrix multiplication -- Learning weights from more than one node -- Backpropagating errors from more output nodes -- Backpropagating errors to more layers -- How do we actually update weights? -- Weight update worked example -- Preparing data -- Python -- Interactive Python = IPython -- A very gentle start with Python -- Neural network with Python -- The MNIST dataset of handwritten numbers -- Your own handwriting -- Inside the mind of a neural network -- Creating new training data: rotations -- Epilogue -- Appendix A : a gentle introduction to calculus -- Appendix B : do it with a Raspberry Pi.