Borrow The Book Of Trees Visualizing Branches Of Knowledge
Download Borrow The Book Of Trees Visualizing Branches Of Knowledge PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Borrow The Book Of Trees Visualizing Branches Of Knowledge book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
The Book of Trees
Author: Manuel Lima
language: en
Publisher: Princeton Architectural Press
Release Date: 2014-04-08
Our critically acclaimed bestseller Visual Complexity was the first in-depth examination of the burgeoning field of information visualization. Particularly noteworthy are the numerous historical examples of past efforts to make sense of complex systems of information. In this new companion volume, The Book of Trees, data viz expert Manuel Lima examines the more than eight hundred year history of the tree diagram, from its roots in the illuminated manuscripts of medieval monasteries to its current resurgence as an elegant means of visualization. Lima presents two hundred intricately detailed tree diagram illustrations on a remarkable variety of subjects—from some of the earliest known examples from ancient Mesopotamia to the manuscripts of medieval monasteries to contributions by leading contemporary designers. A timeline of capsule biographies on key figures in the development of the tree diagram rounds out this one-of-a-kind visual compendium.
Data Science and Analytics with Python
Data Science and Analytics with Python is designed for practitioners in data science and data analytics in both academic and business environments. The aim is to present the reader with the main concepts used in data science using tools developed in Python, such as SciKit-learn, Pandas, Numpy, and others. The use of Python is of particular interest, given its recent popularity in the data science community. The book can be used by seasoned programmers and newcomers alike. The book is organized in a way that individual chapters are sufficiently independent from each other so that the reader is comfortable using the contents as a reference. The book discusses what data science and analytics are, from the point of view of the process and results obtained. Important features of Python are also covered, including a Python primer. The basic elements of machine learning, pattern recognition, and artificial intelligence that underpin the algorithms and implementations used in the rest of the book also appear in the first part of the book. Regression analysis using Python, clustering techniques, and classification algorithms are covered in the second part of the book. Hierarchical clustering, decision trees, and ensemble techniques are also explored, along with dimensionality reduction techniques and recommendation systems. The support vector machine algorithm and the Kernel trick are discussed in the last part of the book. About the Author Dr. Jesús Rogel-Salazar is a Lead Data scientist with experience in the field working for companies such as AKQA, IBM Data Science Studio, Dow Jones and others. He is a visiting researcher at the Department of Physics at Imperial College London, UK and a member of the School of Physics, Astronomy and Mathematics at the University of Hertfordshire, UK, He obtained his doctorate in physics at Imperial College London for work on quantum atom optics and ultra-cold matter. He has held a position as senior lecturer in mathematics as well as a consultant in the financial industry since 2006. He is the author of the book Essential Matlab and Octave, also published by CRC Press. His interests include mathematical modelling, data science, and optimization in a wide range of applications including optics, quantum mechanics, data journalism, and finance.
Visual Complexity
Author: Manuel Lima
language: en
Publisher: Princeton Architectural Press
Release Date: 2013-09-10
Manuel Lima's smash hit Visual Complexity is now available in paperback. This groundbreaking 2011 book—the first to combine a thorough history of information visualization with a detailed look at today's most innovative applications—clearly illustrates why making meaningful connections inside complex data networks has emerged as one of the biggest challenges in twenty-first-century design. From diagramming networks of friends on Facebook to depicting interactions among proteins in a human cell, Visual Complexity presents one hundred of the most interesting examples of informationvisualization by the field's leading practitioners.