Annotated Algorithms in Python



Download free course Annotated Algorithms in Python, pdf file on 388 pages by by Massimo Di Pierro.
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.

The algorithms you will learn can be applied to different disciplines. Throughout history, it is not uncommon that an algorithm invented by a physicist would find application in, for example, biology or finance.

Table of contents

  • Introduction
  • Main Ideas
  • About Python
  • Book Structure
  • Book Software
  • Overview of the Python Language
  • About Python
  • Types of variables
  • Python control flow statements
  • Classes
  • File input/output
  • How to import modules
  • Theory of Algorithms
  • Order of growth of algorithms
  • Recurrence relations
  • Types of algorithms
  • Timing algorithms
  • Data structures
  • Tree algorithms
  • Graph algorithms
  • Greedy algorithms
  • Artificial intelligence and machine learning
  • Long and infinite loops
  • Numerical Algorithms
  • Well-posed and stable problems
  • Approximations and error analysis
  • Standard strategies
  • Linear algebra
  • Sparse matrix inversion
  • Solvers for nonlinear equations
  • Optimization in one dimension
  • Functions of many variables
  • Nonlinear fitting
  • Integration
  • Fourier transforms
  • Differential equations
  • Probability and Statistics
  • Probability
  • Combinatorics and discrete random variables
  • Random Numbers and Distributions
  • Randomness, determinism, chaos and order
  • Real randomness
  • Entropy generators
  • Pseudo-randomness
  • Parallel generators and independent sequences
  • Generating random numbers from a given distribution
  • Probability distributions for continuous random variables
  • Resampling
  • Binning
  • Monte Carlo Simulations
  • Introduction
  • Error analysis and the bootstrap method
  • A general purpose Monte Carlo engine
  • Monte Carlo integration
  • Stochastic, Markov, Wiener, and processes
  • Option pricing
  • Markov chain Monte Carlo (MCMC) and Metropolis
  • Simulated annealing
  • Parallel Algorithms
  • Parallel architectures
  • Parallel metrics
  • Message passing
  • mpi4py
  • Master-Worker and Map-Reduce
  • pyOpenCL
  • Math Review and Notation
Pages : 388
Size : 4.6 MB
File type : PDF
Downloads: 90
Created: 2022-02-01
License: CC BY-NC-ND
Author(s): by Massimo Di Pierro
Annotated Algorithms in Python

Others algorithms Tutorials

Problem Solving with Algorithms and Data Structures

Algorithms

Data Mining and Analysis: Fundamental Concepts and Algorithms

Graph Algorithms

Elementary Algorithms

Others related eBooks about Annotated Algorithms in Python

Getting started with React

This tutorial teaches you how to program with React, a complete PDF document on 139 pages created by StackOverFlow. This course aims to give a solid foundation to React.js by exploring all of its concepts and possibilities, to then facilitate the exploration of the vast ecosystem that revolves arou...

Pro TBB: C++ Parallel Programming with Threading Building Blocks

This book is a modern guide for all C++ programmers to learn Threading Building Blocks (TBB). Written by TBB and parallel programming experts, this book reflects their collective decades of experience in developing and teaching parallel programming with TBB, offering their insights in an approacha...

Clever Algorithms

Download free course Clever Algorithms, pdf file on 454 pages by Jason Brownlee....

Beginner Fortran 90 tutorial

Download Free course and training document about Fortran 90, tutorial on 20 pages for beginners by Guy Munhoven....

A Practical Introduction to Python Programming

Download free course A Practical Introduction to Python Programming, pdf file on 263 pages by by Brian Heinold....

Learning Symfony 3

Symfony 3 tutoririal to download for free, PDF document on 46 pages created by StackOverFlow which teaches you the basics of this framwork. After reading this tutorial you will know the basics of the Symfony 3 framework...

COBOL Programming

Download COBOL tutorial in PDF,a free training courses under 236 pages to learn the basics of COBOL language...

Introduction to Data Science

The demand for skilled data science practitioners in industry, academia, and government is..., download free Data Science tutorial in PDF (722 pages) created by Rafael A Irizarry ....

Algorithms

Algorithms are the lifeblood of computer science. They are the machines that proofs build ..., download free Algorithms tutorial in PDF (472 pages) created by Jeff Erickson ....

So You Want to Learn to Program? - Programming With BASIC-256

Learn to program a computer without the jargon and complexity of many programming books. Suitable for anybody age 10 to 100+ who wants to learn and is ready to experiment. This book engages through media (sound, color, shapes, and text to speech) and then introduces the concepts of structured prog...