Scipy Lecture Notes, 2019. — 659 p.
Tutorials on the scientific Python ecosystem: a quick introduction to central tools and techniques. The different chapters each correspond to a 1 to 2 hours course with
increasing level of expertise, from beginner to expert.
Getting started with Python for sciencePython scientific computing ecosystem.
The Python language.
NumPy: creating and manipulating numerical data.
Matplotlib: plotting.
Scipy: high-level scientific computing.
Getting help and finding documentation.
Advanced topicsAdvanced Python Constructs.
Advanced NumPy.
Debugging code.
Optimizing code.
Sparse Matrices in SciPy.
Image manipulation and processing using Numpy and Scipy.
Mathematical optimization: finding minima of functions.
Interfacing with C.
Packages and applicationsStatistics in Python.
Sympy: Symbolic Mathematics in Python.
Scikit-image: image processing.
Traits: building interactive dialogs.
3D plotting with Mayavi.
scikit-learn: machine learning in Python.
True PDF (A4 format)