Show HN: The Little Notebook for Learning Linear Algebra with Python (little-book-of.github.io)

The Little Notebook is a hands‑on, beginner‑friendly Jupyter-style lab that teaches core linear algebra concepts using Python, NumPy and matplotlib. It walks readers through scalars and vectors, coordinate systems and notation, component access and plotting (using plt.quiver), then demonstrates vector addition, scalar multiplication, linear combinations and span, and vector norms/distances (np.linalg.norm). Each concept is paired with short, runnable code snippets, visualizations (2D arrows, multiple vectors, scatter plots of linear combinations) and “Try it yourself” exercises that encourage experimentation (including notes on 3D vectors and plotting limits). This resource matters for the AI/ML community because linear algebra underpins nearly every model and operation—from embeddings and linear models to PCA and optimization. By coupling algebraic definitions with immediate code and visual intuition (tip‑to‑tail addition, span as a line vs. plane, norm as vector length), the notebook helps practitioners build the geometric intuition needed for debugging, feature design and understanding model behavior. Technical takeaways: use np.array for vectors, index starting at 0, visualize 2D vectors with matplotlib.quiver, compute linear combos with scalar multiplication and addition, explore span by sampling integer coefficients, and measure lengths/distances with np.linalg.norm—simple patterns that scale into more advanced ML tooling.