



    Data Science Fundamentals for Python and MongoDB
Build the foundational data science skills necessary to work with and better understand complex data science algorithms. This exampledriven book provides complete Python coding examples to complement and clarify data science concepts, and enrich the learning experience. Coding examples include visualizations whenever appropriate.... 

Engineering Mechanics for Structures
This is a book about the Mechanics of Solids, Statics, the Strength of Materials, and Elasticity Theory. But that doesn’t mean a thing unless you have had a course in the Mechanics of Solids, Statics, the Strength of Materials, or Elasticity Theory. I assume you have not; let us try again:
This is a book that builds upon what...   Introduction to MATLAB for Engineers
Formerly used mainly by specialists in signal processing and numerical
analysis, MATLAB® in recent years has achieved widespread and enthusiastic
acceptance throughout the engineering community. Many engineering
schools now require a course based entirely or in part on MATLAB early in
the curriculum. MATLAB is programmable and has...   Matrix Transforms for Computer Games and Animation
Matrix transforms are ubiquitous within the world of computer graphics, where they have become an invaluable tool in a programmer’s toolkit for solving everything from 2D image scaling to 3D rotation about an arbitrary axis. Virtually every software system and hardware graphics processor uses matrices to undertake operations such as... 


Complex Variables and the Laplace Transform for Engineers
Widely acclaimed text on essential engineering mathematics. Theory of complex variables, CauchyRiemann equations, conformal mapping, multivalued functions, etc. Also Fourier and Laplace Transform theory, its applications to engineering, including integrals, linear integrodifferential equations, Z Transform, much more. Many excellent...   Applied Interval Analysis
This book is about guaranteed numerical methods based on interval analysis for approximating sets, and about the application of these methods to vast classes of engineering problems. Guaranteed means here that inner and outer approximations of the sets of interest are obtained, which can be made as precise as desired, at the cost of...   Mastering Machine Learning with R
Master machine learning techniques with R to deliver insights for complex projects
About This Book

Get to grips with the application of Machine Learning methods using an extensive set of R packages

Understand the benefits and potential pitfalls of using machine learning methods
... 


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