Over 100 hands-on recipes to sharpen your skills in high-performance numerical computing and data science with Python
Intended to anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, hobbyists… Basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.
IPython is at the heart of the Python scientific stack. With its widely acclaimed web-based notebook, IPython is today an ideal gateway to data analysis and numerical computing in Python.
IPython Interactive Computing and Visualization Cookbook contains many ready-to-use focused recipes for high-performance scientific computing and data analysis. The first part covers programming techniques, including code quality and reproducibility; code optimization; high-performance computing through dynamic compilation, parallel computing, and graphics card programming. The second part tackles data science, statistics, machine learning, signal and image processing, dynamical systems, and pure and applied mathematics.
Chapter 1. A Tour of Interactive Computing with IPython
Chapter 2. Best Practices in Interactive Computing
Chapter 3. Mastering the Notebook
Chapter 4. Profiling and Optimization
Chapter 5. High-performance Computing
Chapter 6. Advanced Visualization
Chapter 7. Statistical Data Analysis
Chapter 8. Machine Learning
Chapter 9. Numerical Optimization
Chapter 10. Signal Processing
Chapter 11. Image and Audio Processing
Chapter 12. Deterministic Dynamical Systems
Chapter 13. Stochastic Dynamical Systems
Chapter 14. Graphs, Geometry, and Geographic Information Systems
Chapter 15. Symbolic and Numerical Mathematics
