"The title says it all. Data is bound by many complex relationships not easily shown in our two-dimensional, spreadsheet filled world. The Shape of Data walks you through this richer view and illustrates how to put it into practice."
—Stephanie Thompson, Data Scientist and Speaker
“The Shape of Data is a novel perspective and phenomenal achievement in the application of geometry to the field of machine learning. It is expansive in scope and contains loads of concrete examples and coding tips for practical implementations, as well as extremely lucid, concise writing to unpack the concepts. Even as a more veteran data scientist who has been in the industry for years now, having read this book I've come away with a deeper connection to and new understanding of my field."
—Kurt Schuepfer, Ph.D., McDonalds Corporation
“A great source for the application of topology and geometry in data science. Topology and geometry advance the field of machine learning on unstructured data, and The Shape of Data does a great job introducing new readers to the subject.”
—Uchenna “Ike” Chukwu, Senior Quantum Developer
"See how data looks not just as lists of numbers but as plots and graphs. The Shape of Data shows the reader how to visualize data sets and discover relations hidden in the numbers and sets. . . . In this age of large data sets and deep learning, data graphics are essential to scientists and engineers—just like this book."
—David S. Mazel, Principal/Manager Systems Engineer, Regulus-Group
"Everyone who works at the border of geometry and Data Science will find the book and invaluable resource and source of inspiration. It is considerate that the R-codes used in the book have readily accessible python codes. "
—Geoffrey Mboya, DPhil (Oxon), Director at Mfano Africa