IPython Interactive Computing and Visualization Cookbook.

Learn to use IPython and Jupyter Notebook for your data analysis and visualization work.

Key Features

• 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
• A comprehensive coverage of scientific computing through many hands-on, example-driven recipes with detailed, step-by-step explanations

Book Description

What you will learn

• Master all features of the Jupyter Notebook
• Code better: write high-quality, readable, and well-tested programs; profile and optimize your code; and conduct reproducible interactive computing experiments
• Visualize data and create interactive plots in the Jupyter Notebook
• Write blazingly fast Python programs with NumPy, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA), parallel IPython, Dask, and more
• Analyze data with Bayesian or frequentist statistics (Pandas, PyMC, and R), and learn from actual data through machine learning (scikit-learn)
• Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
• Simulate deterministic and stochastic dynamical systems in Python
• Familiarize yourself with math in Python using SymPy and Sage: algebra, analysis, logic, graphs, geometry, and probability theory

Who this book is for

This book is intended for anyone interested in numerical computing and data science: students, researchers, teachers, engineers, analysts, and hobbyists. A basic knowledge of Python/NumPy is recommended. Some skills in mathematics will help you understand the theory behind the computational methods.