ThinkDSP

Think DSP is an educational Python project that teaches digital signal processing through executable examples rather than starting with heavy mathematical formalism. It accompanies Allen B. Downey’s book and organizes most lessons as Jupyter notebooks. Readers work directly with waves, spectra, harmonics, filtering, convolution, and other signal-processing concepts. Early exercises show how to decompose sounds, modify frequency components, and synthesize new audio. The repository includes chapter notebooks, solution notebooks, sample sound files, book sources, and reusable Python code. Lessons can run online through Google Colab or Binder, or locally with Conda or Poetry. Its top-down approach is intended for learners who already know basic programming and want a practical route into DSP.