Natural Computing with Python PDF Download

Author: Giancarlo Zaccone
Publisher: BPB Publications
ISBN: 9388511611
Category : Computers
Languages : en
Pages : 300

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Book Description
Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms. DESCRIPTIONÊ Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, youÕll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePyÊ and Cellular Automata techniques such as Game of Life, Langton's ant, etc.Ê The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. KEY FEATURES Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals WHAT WILL YOU LEARN Mastering Artificial Neural Networks Developing Artificial Intelligence systemsÊ Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computation WHO THIS BOOK IS FORÊ This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book. Table of Contents Neural Networks Deep Learning Genetic Programming Swarm Intelligence Cellular Automata Fractals Quantum Computing DNA Computing

Author: A.E. Eiben
Publisher: Springer Science & Business Media
ISBN: 9783540401841
Category : Computers
Languages : en
Pages : 328

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Book Description
The first complete overview of evolutionary computing, the collective name for a range of problem-solving techniques based on principles of biological evolution, such as natural selection and genetic inheritance. The text is aimed directly at lecturers and graduate and undergraduate students. It is also meant for those who wish to apply evolutionary computing to a particular problem or within a given application area. The book contains quick-reference information on the current state-of-the-art in a wide range of related topics, so it is of interest not just to evolutionary computing specialists but to researchers working in other fields.

Author: Joakim Sundnes
Publisher:
ISBN: 3030503569
Category : Computer programming
Languages : en
Pages : 157

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Book Description
This open access book offers an initial introduction to programming for scientific and computational applications using the Python programming language. The presentation style is compact and example-based, making it suitable for students and researchers with little or no prior experience in programming. The book uses relevant examples from mathematics and the natural sciences to present programming as a practical toolbox that can quickly enable readers to write their own programs for data processing and mathematical modeling. These tools include file reading, plotting, simple text analysis, and using NumPy for numerical computations, which are fundamental building blocks of all programs in data science and computational science. At the same time, readers are introduced to the fundamental concepts of programming, including variables, functions, loops, classes, and object-oriented programming. Accordingly, the book provides a sound basis for further computer science and programming studies.

Author: Zaccone Giancarlo
Publisher: BPB Publications
ISBN: 9389328136
Category : Computers
Languages : en
Pages : 293

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Book Description
Step-by-step guide to learn and solve complex computational problems with Nature Inspired algorithms Key features Artificial Neural Networks Deep Learning models using Keras Quantum Computers and Programming Genetic Algorithms, CNN and RNNs Swarm Intelligence Systems Reinforcement Learning using OpenAI Artificial Life DNA computing Fractals Description Natural Computing is the field of research inspired by nature, that allows the development of new algorithms to solve complex problems, leads to the synthesis of natural models, and may result in the design of new computing systems. This book exactly aims to educate you with practical examples on topics of importance associated with research field of Natural computing. The initial few chapters will quickly walk you through Neural Networks while describing deep learning architectures such as CNN, RNN and AutoEncoders using Keras. As you progress further, you'll gain understanding to develop genetic algorithm to solve traveling saleman problem, implement swarm intelligence techniques using the SwarmPackagePy and Cellular Automata techniques such as Game of Life, Langton's ant, etc. The latter half of the book will introduce you to the world of Fractals such as such as the Cantor Set and the Mandelbrot Set, develop a quantum program with the QiSkit tool that runs on a real quantum computing platform, namely the IBM Q Machine and a Python simulation of the Adleman experiment that showed for the first time the possibility of performing computations at the molecular level. What will you learn Mastering Artificial Neural Networks Developing Artificial Intelligence systems Resolving complex problems with Genetic Programming and Swarm intelligence algorithms Programming Quantum Computers Exploring the mathematical world of fractals Simulating complex systems by Cellular Automata Understanding the basics of DNA computationWho this book is for This book is for all science enthusiasts, in particular who want to understand what are the links between computer sciences and natural systems. Interested readers should have good skills in math and python programming along with some basic knowledge of physics and biology. . Although, some knowledge of the topics covered in the book will be helpful, it is not essential to have worked with the tools covered in the book.Table of contents1. Neural Networks2. Deep Learning3. Genetic Algorithms and Programming4. Swarm Intelligence5. Cellular Automata6. Fractals7. Quantum Computing8. DNA ComputingAbout the authorGiancarlo Zaccone has over ten years of experience in managing research projects in scientific and industrial areas.He is a Software and Systems Engineer Consultant at European Space Agency (ESTEC).Giancarlo holds a master's degree in Physics and an advanced master's degree in Scientific Computing at La Sapienza of Rome. Her LinkedIn Profile: https://www.linkedin.com/in/giancarlozaccone/

Author: Nunes de Castro, Leandro
Publisher: IGI Global
ISBN: 1466642548
Category : Computers
Languages : en
Pages : 346

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Book Description
Nature has long provided the inspiration for a variety of scientific discoveries in engineering, biomedicine, and computing, though only recently have these elements of nature been used directly in computational systems. Natural Computing for Simulation and Knowledge Discovery investigates the latest developments in nature-influenced technologies. Within its pages, readers will find an in-depth analysis of such advances as cryptographic solutions based on cell division, the creation and manipulation of biological computers, and particle swarm optimization techniques. Scientists, practitioners, and students in fields such as computing, mathematics, and molecular science will make use of this essential reference to explore current trends in natural computation and advance nature-inspired technologies to the next generation.

Author: Hans Petter Langtangen
Publisher: Springer
ISBN: 3662498871
Category : Computers
Languages : en
Pages : 942

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Book Description
The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen ... does an excellent job of introducing programming as a set of skills in problem solving. He guides the reader into thinking properly about producing program logic and data structures for modeling real-world problems using objects and functions and embracing the object-oriented paradigm. ... Summing Up: Highly recommended. F. H. Wild III, Choice, Vol. 47 (8), April 2010 Those of us who have learned scientific programming in Python ‘on the streets’ could be a little jealous of students who have the opportunity to take a course out of Langtangen’s Primer.” John D. Cook, The Mathematical Association of America, September 2011 This book goes through Python in particular, and programming in general, via tasks that scientists will likely perform. It contains valuable information for students new to scientific computing and would be the perfect bridge between an introduction to programming and an advanced course on numerical methods or computational science. Alex Small, IEEE, CiSE Vol. 14 (2), March /April 2012 “This fourth edition is a wonderful, inclusive textbook that covers pretty much everything one needs to know to go from zero to fairly sophisticated scientific programming in Python...” Joan Horvath, Computing Reviews, March 2015

Author: Gisele L. Pappa
Publisher: Springer
ISBN: 9783642261251
Category : Computers
Languages : en
Pages : 0

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Book Description
Data mining is a very active research area with many successful real-world app- cations. It consists of a set of concepts and methods used to extract interesting or useful knowledge (or patterns) from real-world datasets, providing valuable support for decision making in industry, business, government, and science. Although there are already many types of data mining algorithms available in the literature, it is still dif cult for users to choose the best possible data mining algorithm for their particular data mining problem. In addition, data mining al- rithms have been manually designed; therefore they incorporate human biases and preferences. This book proposes a new approach to the design of data mining algorithms. - stead of relying on the slow and ad hoc process of manual algorithm design, this book proposes systematically automating the design of data mining algorithms with an evolutionary computation approach. More precisely, we propose a genetic p- gramming system (a type of evolutionary computation method that evolves c- puter programs) to automate the design of rule induction algorithms, a type of cl- si cation method that discovers a set of classi cation rules from data. We focus on genetic programming in this book because it is the paradigmatic type of machine learning method for automating the generation of programs and because it has the advantage of performing a global search in the space of candidate solutions (data mining algorithms in our case), but in principle other types of search methods for this task could be investigated in the future.

Author: Daniel Shiffman
Publisher: No Starch Press
ISBN: 1718503717
Category : Computers
Languages : en
Pages : 642

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Book Description
All aboard The Coding Train! This beginner-friendly creative coding tutorial is designed to grow your skills in a fun, hands-on way as you build simulations of real-world phenomena with “The Coding Train” YouTube star Daniel Shiffman. What if you could re-create the awe-inspiring flocking patterns of birds or the hypnotic dance of fireflies—with code? For over a decade, The Nature of Code has empowered countless readers to do just that, bridging the gap between creative expression and programming. This innovative guide by Daniel Shiffman, creator of the beloved Coding Train, welcomes budding and seasoned programmers alike into a world where code meets playful creativity. This JavaScript-based edition of Shiffman’s groundbreaking work gently unfolds the mysteries of the natural world, turning complex topics like genetic algorithms, physics-based simulations, and neural networks into accessible and visually stunning creations. Embark on this extraordinary adventure with projects involving: A physics engine: Simulate the push and pull of gravitational attraction. Flocking birds: Choreograph the mesmerizing dance of a flock. Branching trees: Grow lifelike and organic tree structures. Neural networks: Craft intelligent systems that learn and adapt. Cellular automata: Uncover the magic of self-organizing patterns. Evolutionary algorithms: Play witness to natural selection in your code. Shiffman’s work has transformed thousands of curious minds into creators, breaking down barriers between science, art, and technology, and inviting readers to see code not just as a tool for tasks but as a canvas for boundless creativity. Whether you’re deciphering the elegant patterns of natural phenomena or crafting your own digital ecosystems, Shiffman’s guidance is sure to inform and inspire. The Nature of Code is not just about coding; it’s about looking at the natural world in a new way and letting its wonders inspire your next creation. Dive in and discover the joy of turning code into art—all while mastering coding fundamentals along the way. NOTE: All examples are written with p5.js, a JavaScript library for creative coding, and are available on the book's website.

Author: David Fagan
Publisher: Springer
ISBN: 3030040704
Category : Computers
Languages : en
Pages : 478

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Book Description
This book constitutes the refereed proceedings of the 7th International Conference on Theory and Practice of Natural Computing, TPNC 2017, held in Dublin, Ireland, in December 2018. The 35 full papers presented in this book, together with one invited talk, were carefully reviewed and selected from 69 submissions. The papers are organized around the following topical sections: applications of natural computing as algorithms, bioinformatics, control, cryptography, design, economics. The more theoretical contributions handle with artificial chemistry, artificial immune systems, artificial life, cellular automata, cognitive computing, cognitive engineering, cognitive robotics, collective behaviour, complex systems, computational intelligence, computational social science, computing with words, developmental systems, DNA computing, DNA nanotechnology, evolutionary algorithms, evolutionary computing, evolutionary game theory, fractal geometry, fuzzy control, fuzzy logic, fuzzy sets, fuzzy systems, genetic algorithms, genetic programming, granular computing, heuristics, intelligent agents, intelligent systems, machine intelligence, molecular programming, neural computing, neural networks, quantum communication, quantum computing, rough sets, self-assembly.

Author: Steven Bird
Publisher: "O'Reilly Media, Inc."
ISBN: 0596555717
Category : Computers
Languages : en
Pages : 506

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Book Description
This book offers a highly accessible introduction to natural language processing, the field that supports a variety of language technologies, from predictive text and email filtering to automatic summarization and translation. With it, you'll learn how to write Python programs that work with large collections of unstructured text. You'll access richly annotated datasets using a comprehensive range of linguistic data structures, and you'll understand the main algorithms for analyzing the content and structure of written communication. Packed with examples and exercises, Natural Language Processing with Python will help you: Extract information from unstructured text, either to guess the topic or identify "named entities" Analyze linguistic structure in text, including parsing and semantic analysis Access popular linguistic databases, including WordNet and treebanks Integrate techniques drawn from fields as diverse as linguistics and artificial intelligence This book will help you gain practical skills in natural language processing using the Python programming language and the Natural Language Toolkit (NLTK) open source library. If you're interested in developing web applications, analyzing multilingual news sources, or documenting endangered languages -- or if you're simply curious to have a programmer's perspective on how human language works -- you'll find Natural Language Processing with Python both fascinating and immensely useful.