Mastering social media mining with python, Bonzanini, Marco

Harness IPython for powerful scientific computing and Python data visualization with this collection of more than 100 practical data science recipes

Key Features

• Leverage the new features of the IPython notebook for interactive web-based big data analysis 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

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.

What you will learn

• Code better by writing high-quality, readable, and well-tested programs; profiling and optimizing your code, and conducting reproducible interactive computing experiments
• Master all of the new features of the IPython notebook, including the interactive HTML/JavaScript widgets
• Analyze data with Bayesian and frequentist statistics (Pandas, PyMC, and R), and learn from data with machine learning (scikit-learn)
• Gain valuable insights into signals, images, and sounds with SciPy, scikit-image, and OpenCV
• Learn how to write blazingly fast Python programs with NumPy, PyTables, ctypes, Numba, Cython, OpenMP, GPU programming (CUDA and OpenCL), parallel IPython, MPI, and many more