Ebook: Python data analysis cookbook: over 140 practical recipes to help you make sense of your data with ease and build production-ready data apps

About This BookAnalyze Big Data sets, create attractive visualizations, and manipulate and process various data typesPacked with rich recipes to help you learn and explore amazing algorithms for statistics and machine learningAuthored by Ivan Idris, expert in python programming and proud author of eight highly reviewed booksWho This Book Is For This book is hands-on and low on theory. You should have better than beginner Python knowledge and have some knowledge of linear algebra, calculus, machine learning and statistics. Ideally, you would have read Python Data Analysis, but this is not a requirement. I also recommend the following books: Building Machine Learning Systems with Python by Willi Richert and Luis Pedro Coelho, 2013Learning NumPy Array by Ivan Idris, 2014Learning scikit-learn: Machine Learning in Python by Guillermo Moncecchi, 2013Learning SciPy for Numerical and Scientific Computing by Francisco J. Blanco-Silva, 2013Matplotlib for Python Developers by Sandro Tosi, 2009NumPy Beginner's Guide - Third Edition by Ivan Idris, 2015NumPy Cookbook - Second Edition by Ivan Idris, 2015Parallel Programming with Python by Jan Palach, 2014Python Data Visualization Cookbook by Igor Milovanovic, 2013Python for Finance by Yuxing Yan, 2014Python Text Processing with NLTK 2.0 Cookbook by Jacob Perkins, 2010What You Will LearnSet up reproducible data analysisClean and transform dataApply advanced statistical analysisCreate attractive data visualizationsWeb scrape and work with databases, Hadoop, and SparkAnalyze images and time series dataMine text and analyze social networksUse machine learning and evaluate the resultsTake advantage of parallelism and concurrencyIn Detail Data analysis is a rapidly evolving field, and Python has evolved as the primary language for data science, including topics on: data analysis, visualization, and machine learning.