Scripts to generate the figures in the book Quantum Machine Learning: What Quantum Computing Means to Data Mining
TeX Python
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LICENSE
README.md
adiabatic_memory.py
adiabatic_process.py
bell_state_generator.tex
bifurcation_graph.tex
bloch_sphere.py
chimera.tex
cnot_gate.tex
common_graphics_settings.py
convex_loss_functions.py
feedforward.tex
fredkin_gate.tex
graphics_utils.py
grover_operator.tex
grover_search.tex
hadamard_gate.tex
hopfield.tex
meter.svg
nonconvex_loss_functions.py
perceptron.tex
quantum_annealing.py
quantum_neural_network.tex
quantum_parallelism.tex
quantum_swap.tex
quantum_swap_gate.tex
quantum_tunneling.py
supervised.py
support_vectors.py
swap_test.tex
toffoli_gate.tex
transductive.py
unsupervised.py
vc_dimension_line.py
vc_dimension_sine.py
xor_problem.py

README.md

This repository stores the source code of the figures in the book Quantum Machine Learning: What Quantum Computing Means to Data Mining. More information on the book is here:

http://peterwittek.com/book

Dependencies

The LaTeX files use tikz, which should be standard in most TeX distribution.

The Python files use matplotlib, numpy, and seaborn. Furthermore, LaTeX is used for rendering text, hence a LaTeX compiler should be in the path. Plotting the Bloch sphere also requires the QuTIP toolbox.