• Title Annotated Algorithms in Python: with Applications in Physics, Biology, and Finance
• Author(s) Massimo Di Pierro
• Publisher: Experts4Solutions (November 26, 2013)
• License(s): CC BY-NC-ND 3.0
• Hardcover/Paperback 388 pages
• eBook PDF (388 pages)
• Language: English
• ISBN-10: 0991160401
• ISBN-13: 978-0991160402
• Share This:  

Book Description

This book is assembled from lectures given by the author over a period of 10 years at the School of Computing of DePaul University. The lectures cover multiple classes, including Analysis and Design of Algorithms, Scientific Computing, Monte Carlo Simulations, and Parallel Algorithms. These lectures teach the core knowledge required by any scientist interested in numerical algorithms and by students interested in computational finance.

• Massimo Di Pierro is Associate Professor at the School of Computing of DePaul University in Chicago. He has a Ph.D. in High Energy Theoretical Physics from the University of Southampton (UK). His expertise is in Numerical Algorithms, Parallel Computing, and Web Application Development.

• Amazon

• Python Programming
• Algorithms and Data Structures
• Computational Complexity

• Annotated Algorithms in Python: with Applications in Physics, Biology, and Finance
• The Mirror Site (1) - PDF
• Book Homepage

• Algorithmic Problem Solving with Python (John B. Schneider)

  This book uses Python to introduce folks to programming and algorithmic thinking. It is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques.

• Problem Solving with Algorithms/Data Structures using Python

  This is a textbook about computer science. It is also about Python. However, there is much more. The tools and techniques that you learn here will be applied over and over as you continue your study of computer science.

• Data Structures/Algorithms with OPP Design Patterns in Python

  It promotes object-oriented design using Python and illustrates the use of the latest object-oriented design patterns. Virtually all the data structures are discussed in the context of a single class hierarchy.

• O'Reilly® Think Python, 2nd Edition (Allen B. Downey)

  This hands-on guide takes you through the Python programming language a step at a time, beginning with basic programming concepts before moving on to functions, recursion, data structures, and object-oriented design. 2nd edition updated for Python 3.

• The Recursive Book of Recursion using Python (Al Sweigart)

  Recursion has an intimidating reputation. This book uses Python and JavaScript examples to teach the basics of recursion, exposing the ways that it's often poorly taught and clarifying the fundamental principles of all recursive algorithms.

• Classic Computer Science Problems in Python (David Kopec)

  This book deepens your knowledge of problem-solving techniques from the realm of computer science by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more.

• CS for All: An Introduction to Computer Science using Python

  To provide an introduction to computer science as an intellectually rich and vibrant field rather than focusing exclusively on computer programming. It emphasizes concepts and problem-solving over syntax and programming language features.

• Principles of Algorithmic Problem Solving (Johan Sannemo)

  The algorithmic approach to solving problems in computer technology is an essential tool. This book presents a readable, entertaining, and energetic book that will motivate and challenge students to open their minds to the algorithmic nature of problem solving.