From the newest IPython/Jupyter capabilities to the most cutting-edge tactics, this book provides a wealth of ready-to-use, targeted recipes for high-performance scientific computing and data analysis.
These recipes will help you build better, quicker code. You will use these cutting-edge techniques to illustrate concepts in applied mathematics, scientific modeling, and machine learning in a variety of real-world cases.
It is for students, researchers, professors, engineers, analysts, and amateurs who are interested in numerical computing and data science. NumPy and Python fundamentals are advised. You can better understand the theory underlying the computational approaches if you have some mathematical knowledge.
- Leverage the Jupyter Notebook for interactive data science and visualization
- Become an expert in high-performance computing and visualization for data analysis and scientific modeling
- Comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations