From Curve Fitting to Machine Learning

This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or

The analysis of experimental data is at heart of science from its beginnings. But it was the advent of digital computers that allowed the execution? of highly non-linear and increasingly complex data

First published in 1961, this book provides information on the methods of treating series of observations, the field covered embraces portions of both statistics and numerical analysis. Originally intended as an introduction to the topic aimed at students and graduates in physics, the types of observation discussed reflect the standard routine work of the time in the physical sciences. The text partly reflects an aim to offer a better balance between theory and practice, reversing the tendency of books on numerical analysis to omit numerical examples illustrating the applications of the methods. This book will be of value to anyone with an interest in the theoretical development of its field.

Introductory statistics texts do not consider non-linear regression, and textbooks that do are advanced treatments for mathematicians. So pharmacological researchers Motulsky (U. of California-San Die

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