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This book covers methods for evaluation of experimental data commonly encountered in science and engineering. Measurements of quantities that vary in a... Læs mere
Accordingly, this textbook is not meant to cover the whole range of this high-performance technical programming environment, but to motivate first- and... Læs mere
Deep Learning with R introduces deep learning and neural networks using the R programming language. The book starts with an introduction to machine learning and moves on to... Læs mere
The author clearly explains all the theory students will need to avoid mistakes, understand what regressions are really doing, and evaluate analyses performed by... Læs mere
This new edition features practice exercises in every chapter, and new chapters on topics such as dynamic programming and heaps and tries. Get the hands-on info you need to master data structures and algorithms for your day-to-day work.
This book is designed for the first time or occasional SAS user who needs immediate guidance in navigating, exploring, visualizing, cleaning and reporting on... Læs mere
"Provides a comprehensive and rigorous presentation of descriptive statistics and probability theory that has been extensively classroom tested"--
Features easy-to-follow insight and clear guidelines to perform data analysis using IBM SPSS(R) Performing Data Analysis Using IBM SPSS(R) uniquely addresses the presented statistical procedures with an example problem, detailed analysis, and the related data sets.
Nonlinear Parameter Optimization Using R John C.
This book introduces artificial neural networks to students and professionals. It covers the theory and applications in statistical learning methods with concrete Python code examples.