Free Data Infrastructure Research Library Books & Tutorials. Read online or download these free Data Infrastructure Research Library eBooks, lecture notes & tutorials.
This book's goal is to educate students on software development and programming through the perspective of data exploration. Consider the Python programming language as your instrument for handling data issues that go beyond what a spreadsheet can handle. ...
For upper-level undergraduate and graduate students in engineering, physics, and mathematics, this introduction to combinatorics—the theoretical underpinning of the relationship between computer science and mathematics—is appropriate.
EXPLORING DISCRETE DYNAMICS is a thorough manual for using the renowned software Discrete Dynamics Laboratory (DDLab), which is frequently used in research and education, to study discrete dynamical networks and cellular automata.
This book, written by a renowned expert in quantum computing theory Scott Aaronson, takes readers on a journey through some of the most complex concepts in physics, computer science, and mathematics.
The concept of "variations" has undergone significant development in relation to applications in optimization, equilibrium, and control since its beginnings in the minimization of integral functionals.
The most recent theory and applications in optimization are covered in this book. Beginning with a thorough discussion of linear programming, it then moves on to convex analysis, network flows, integer programming, quadratic programming, and convex optimization, putting an...
a basic introduction to algorithms and data structures with emphasis on how they apply to graphics and geometry.
This book was incredibly helpful for comprehending the algorithms quickly. There are sufficient examples of each algorithm in this book. It was designed with the intention of giving pupils a thorough understanding of algorithms.
This is a heuristic algorithm online textbook. Classes of Problems, Integer Programming, Enumeration Techniques, Dynamic Programming, Approximate Solutions, Local Optimization, and Natural Models are all listed in the table of contents.
This book is ideal if you want to upgrade Python 2 code or need assistance writing programs in Python 3.