Deep Learning (Adaptive Computation and Machine Learning series)
Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers...
Statistics and Machine Learning in Python
This book illustrates the fundamental concepts that link statistics and machine learning, so that the reader can not only employ statistical and machine learning models using modern Python modules, but...
An Introduction to Statistical Learning: with Applications in Python
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged...
An Introduction to Statistical Learning, 2nd Edition: with Applications in R
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged...
Elementary Calculus
This textbook covers calculus of a single variable, suitable for a year-long (or two-semester) course. Chapters 1-5 cover Calculus I, while Chapters 6-9 cover Calculus II. The book is designed...
Calculus in Context
For courses currently engaged, or leaning toward calculus reform. Callahan fully embraces the calculus reform movement in technology and pedagogy, while taking it a step further with a unique organization...
CLP-4 Vector Calculus
This textbook covers Vector Calculus. There are chapters on curves, vector fields, surface integrals and integral theorems (such as the divergence theorem).
CLP-3 Multivariable Calculus
This textbook covers multivariable Calculus. There are chapters on vectors and geometry in 2 and 3 dimensions, partial derivatives, and multivariable integrals.
CLP-2 Integral Calculus
This textbook covers single variable Integral Calculus.
CLP-1 Differential Calculus
This textbook covers single variable Differential Calculus.