This is an excellent resource for building mathematical intuition through code. Python's combination of readable syntax and powerful libraries (NumPy, SymPy, Matplotlib) makes it ideal for exploring concepts like linear algebra, calculus, and discrete math interactively.
One approach I've found effective: start with a conjecture, visualize it with matplotlib, then prove it formally. The instant feedback loop helps develop both computational thinking and mathematical rigor. Tools like Jupyter notebooks make this workflow seamless.
For anyone interested in similar resources, "Mathematics for Machine Learning" by Deisenroth et al. and 3Blue1Brown's linear algebra series complement this beautifully by bridging theory and computation.
One approach I've found effective: start with a conjecture, visualize it with matplotlib, then prove it formally. The instant feedback loop helps develop both computational thinking and mathematical rigor. Tools like Jupyter notebooks make this workflow seamless.
For anyone interested in similar resources, "Mathematics for Machine Learning" by Deisenroth et al. and 3Blue1Brown's linear algebra series complement this beautifully by bridging theory and computation.