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Principles Of Soft Computing Using Python Programming
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Book Synopsis Principles of Soft Computing Using Python Programming by : Gypsy Nandi
Download or read book Principles of Soft Computing Using Python Programming written by Gypsy Nandi and published by John Wiley & Sons. This book was released on 2023-11-28 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: Principles of Soft Computing Using Python Programming An accessible guide to the revolutionary techniques of soft computing Soft computing is a computing approach designed to replicate the human mind’s unique capacity to integrate uncertainty and imprecision into its reasoning. It is uniquely suited to computing operations where rigid analytical models will fail to account for the variety and ambiguity of possible solutions. As machine learning and artificial intelligence become more and more prominent in the computing landscape, the potential for soft computing techniques to revolutionize computing has never been greater. Principles of Soft Computing Using Python Programming provides readers with the knowledge required to apply soft computing models and techniques to real computational problems. Beginning with a foundational discussion of soft or fuzzy computing and its differences from hard computing, it describes different models for soft computing and their many applications, both demonstrated and theoretical. The result is a set of tools with the potential to produce new solutions to the thorniest computing problems. Readers of Principles of Soft Computing Using Python Programming will also find: Each chapter accompanied with Python codes and step-by-step comments to illustrate applications Detailed discussion of topics including artificial neural networks, rough set theory, genetic algorithms, and more Exercises at the end of each chapter including both short- and long-answer questions to reinforce learning Principles of Soft Computing Using Python Programming is ideal for researchers and engineers in a variety of fields looking for new solutions to computing problems, as well as for advanced students in programming or the computer sciences.
Book Synopsis An Introduction to Python Programming: A Practical Approach by : Dr. Krishna Kumar Mohbey
Download or read book An Introduction to Python Programming: A Practical Approach written by Dr. Krishna Kumar Mohbey and published by BPB Publications. This book was released on 2021-08-26 with total page 468 pages. Available in PDF, EPUB and Kindle. Book excerpt: step-by-step approach to Python programming with machine learning fundamental and theoretical principles. KEY FEATURES ● Introduces readers to Python programming in a very simple way. ● Extensive practical demonstration of Python concepts using numerous examples. ● Implementation of machine learning in Python using hands-on techniques. DESCRIPTION The book ‘Introduction to Python Programming: A Practical Approach’ lays out a path for readers who want to pursue a career in the field of computer software development. It covers the fundamentals of Python programming as well as machine learning principles. Students will benefit from the examples that are included with each concept, which will aid them in understanding the concept. This book provides a practical understanding of Python programming using numerous programs and examples. It also develops problem-solving and code-writing abilities for the readers. This book covers Python fundamentals, operators, and data structures such as strings, lists, dictionaries, and tuples. It also contains information on file and exception handling. The implementation of a machine learning model has also been included in this book. With the help of this book, students and programmers can improve their programming skills as well as their ability to sprint towards a rewarding career. WHAT YOU WILL LEARN ● Learn Python concepts, operators, and data structures. ● Learn the properties and operations of lists, tuples, and dictionaries. ● Write Python code to solve specific issues. ● Write Python code to handle disk files and exceptions. ● Work with OOPS properties like classes, objects, constructors, inheritance, and polymorphism. ● Use machine learning for classification, regression, prediction, and clustering. WHO THIS BOOK IS FOR This book is intended for current and aspiring emerging technology professionals, students, and anyone else who wishes to better understand the Python programming language and machine learning concepts. TABLE OF CONTENTS 1. Chapter 1: Basics of Python Programming 2. Chapter 2: Operators and Expressions 3. Chapter 3: Control Flow Statements 4. Chapter 4: Functions 5. Chapter 5: Strings 6. Chapter 6: Lists 7. Chapter 7: Tuple 8. Chapter 8: Dictionaries 9. Chapter 9: File Handling 10. Chapter 10: Exception Handling, Modules, and Packages 11. Chapter 11: Object-oriented Programming 12. Chapter 12: Machine Learning with Python 13. Chapter 13: Clustering with Python
Book Synopsis The Practice of Computing Using Python by : William F. Punch
Download or read book The Practice of Computing Using Python written by William F. Punch and published by Addison-Wesley. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A problem-solving approach to programming with Python.The Practice of Computing using Python, first editionis intended to teach problem solving within the context of CS1 to both majors and non-majors using Python as a vehicle. As such the authors cover general concepts like hardware, complexity, and software engineering as well as general concepts of programming using the Python language. In the end, if a student takes no other programming course than one such as this, they can be productive programmers who understand general principles of computation and can produce useful, meaningful results in their respective fields of study. The Study of Computer Science; Starting to Program–Beginnings, Control, Algorithms and Program Development; Organizing: Data Structures and Functions–Working with Strings, Functions–QuickStart, Lists and Tuples, Dictionaries and Sets, Files; Classes: Making Your Own Data Structures & Algorithms–Program Development with Classes; Becoming a Better Programmer–Exceptions and Exception Handling, Testing, Recursion-another control mechanism, Getting and Using Python, Simple Drawing with Turtle Graphics, Plotting and Numeric Tools, Python 3.0. Anyone interested in learning Python or computer programming skills in general.
Book Synopsis Soft Computing and Machine Learning with Python by : Zoran Gacovski
Download or read book Soft Computing and Machine Learning with Python written by Zoran Gacovski and published by Arcler Press. This book was released on 2018-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: A definition states that the machine learning is a discipline that allows the computers to learn without explicit programming. The challenge in machine learning is how to accurately (algorithmic) describe some kinds of tasks that people can easily solve (for example face recognition, speech recognition etc.). Such algorithms can be defined for certain types of tasks, but they are very complex and/or require large knowledge base (e.g. machine translation MT). In many of the areas - data are continuously collected in order to get "some knowledge out of them" for example - in medicine (patient data and therapy), in marketing (the users / customers and what they buy, what are they interested in, how products are rated etc.). Data analysis of this scale requires approaches that will allow you to discover patterns and dependences among the data, that are neither known, nor obvious, but can be useful (data mining). Information retrieval - IR, is finding existing information as quickly as possible. For example, web browser - finds page within the (large) set of the entire WWW. Machine Learning - ML, is a set of techniques that generalize existing knowledge of the new information, as precisely as possible. An example is the speech recognition. Data mining - DM, primarily relates to the disclosure of something hidden within the data, some new dependence, which have not previously been known. Example is CRM - the customer analysis. Python is high-level programming language that is very suitable for web development, programming of games, and data manipulation / machine learning applications. It is object-oriented language and interpreter as well, allowing the source code to execute directly (without compiling). This edition covers machine learning theory and applications with Python, and includes chapters for soft computing theory, machine learning techniques/applications, Python language details, and machine learning examples with Python. Book jacket.
Book Synopsis Python for Beginners by : Robert Campbell
Download or read book Python for Beginners written by Robert Campbell and published by . This book was released on 2021-01-28 with total page 70 pages. Available in PDF, EPUB and Kindle. Book excerpt: ARE YOU LOOKING FOR A COMPLETE GUIDE PYTHON? THEN KEEP READING... Programming has come a long way. The world of programming may have started quite some time ago; it was only a couple of decades ago that it gained attention from computer experts from across the globe. This sudden shift saw some great minds who contributed to the entire age of programming far greater than most. We saw the great GNU project take shape during this era. We came across the rather brilliant Linux. New programming languages were born as well, and people certainly enjoyed these to the utmost. While most of these programming languages worked, there was something that was missing. Surely, something could be done to make coding a less tedious task to do and carry out. That is exactly what a revolutionary new language, named after Monty Python's Flying Circus, did for the world. Immediately, coding became so much easier for programmers. The use of this language started gaining momentum, and today, it is set to overtake the only language that stands before it to claim the prestigious spot of being the world's most favored language. This language was the brainchild of Guido Van Rossum. Created in the year 1991, Python has become a byword for efficient and user-friendly programming. This language is what connected the dots and gave programmers the much-needed ease of coding that they have since been yearning for. Naturally, the language was received well by the programming community. Today, it is one of the most important languages for both professionals and students who aim to excel in fields like Machine Learning, automation, artificial intelligence, and so much more. This book covers: - Python - The First Impressions - Getting ready for Python - The world of Variables and Operators - Making Your Program Interactive - List, Tuples and dictionaries - Functions and Modules - Working with Files - Object Oriented Programming And much more. Ready to get started? Click "Buy Now"!
Book Synopsis Quantum Computing with Python by : Jason Test
Download or read book Quantum Computing with Python written by Jason Test and published by Independently Published. This book was released on 2021-03-17 with total page 566 pages. Available in PDF, EPUB and Kindle. Book excerpt: *KINDLE VERSION Discounted at $ 9.99 instead of $ 14.99... Get QUANTUM PHYSICS section for FREE!! "Master the best methods for PYTHON. Learn how to programming as a pro and get positive ROI in 7 days with data science and machine learning" Are you looking for a super-fast computer programming course? Would you like to learn the Python Programming Language in 7 days? Do you want to increase your business thanks to the web applications? Finally on launch the most complete Python+Quantum Physics guide with 4 Manuscripts in 1 book! This is a challenging tool to find real help with many unique contents that indirectly will answer to your doubts: 1-Python for beginners 2-Python for Data Science 3-Python Crash Course and special and FREE section: 4-Quantum Physics for beginners QUANTUM COMPUTING WITH PYTHON will introduce you many selected practices for coding. You will discover as a beginner the world of data science, machine learning and artificial intelligence. The following list is just a tiny fraction of what you will learn in this collection bundle. 1) Python for beginners ✓ The basics of Python programming ✓ Easy-to-follow steps for reading and writing codes. ✓ 3 best strategies with NumPy, Pandas, Matplotlib 2) Python for Data science ✓3 reasons why Python is fundamental for Data Science ✓How to use Python Data Analysis in your business ✓ How to set up the Python environment for Data Science ✓Most important Machine Learning Algorithms 3) Python Crash Course ✓ A Proven Method to Write your First Program in 7 Days ✓The One Thing You Need to Debug your Codes in Python ✓5 Practical exercises to start programming 4) Quantum Physics for beginners ✓The law and principles of quantum physics and the law of attraction; ✓The power of quantum ✓Differences between Quantum cryptography and Quantum computers Examples and step-by-step guides will guide you during the code-writing learning process. The description of each topic is crystal-clear and you can easily practice with related exercises. You will also learn all the 3 best tricks of writing codes with point by point descriptions of the code elements. Even if you have never written a programming code before, you will quickly grasp the basics thanks to visual charts and guidelines for coding. If you really wish to to learn Python and master its language, please click the BUY NOW button.
Book Synopsis Python Programming by : John M. Zelle
Download or read book Python Programming written by John M. Zelle and published by Franklin, Beedle & Associates, Inc.. This book was released on 2004 with total page 533 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is suitable for use in a university-level first course in computing (CS1), as well as the increasingly popular course known as CS0. It is difficult for many students to master basic concepts in computer science and programming. A large portion of the confusion can be blamed on the complexity of the tools and materials that are traditionally used to teach CS1 and CS2. This textbook was written with a single overarching goal: to present the core concepts of computer science as simply as possible without being simplistic.
Book Synopsis Scientific Computing with Python - Second Edition by : CLAUS. FUHRER
Download or read book Scientific Computing with Python - Second Edition written by CLAUS. FUHRER and published by . This book was released on 2021-07-23 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage this example-packed, comprehensive guide for all your Python computational needs Key Features: Learn the first steps within Python to highly specialized concepts Explore examples and code snippets taken from typical programming situations within scientific computing. Delve into essential computer science concepts like iterating, object-oriented programming, testing, and MPI presented in strong connection to applications within scientific computing. Book Description: Python has tremendous potential within the scientific computing domain. This updated edition of Scientific Computing with Python features new chapters on graphical user interfaces, efficient data processing, and parallel computing to help you perform mathematical and scientific computing efficiently using Python. This book will help you to explore new Python syntax features and create different models using scientific computing principles. The book presents Python alongside mathematical applications and demonstrates how to apply Python concepts in computing with the help of examples involving Python 3.8. You'll use pandas for basic data analysis to understand the modern needs of scientific computing, and cover data module improvements and built-in features. You'll also explore numerical computation modules such as NumPy and SciPy, which enable fast access to highly efficient numerical algorithms. By learning to use the plotting module Matplotlib, you will be able to represent your computational results in talks and publications. A special chapter is devoted to SymPy, a tool for bridging symbolic and numerical computations. By the end of this Python book, you'll have gained a solid understanding of task automation and how to implement and test mathematical algorithms within the realm of scientific computing. What You Will Learn: Understand the building blocks of computational mathematics, linear algebra, and related Python objects Use Matplotlib to create high-quality figures and graphics to draw and visualize results Apply object-oriented programming (OOP) to scientific computing in Python Discover how to use pandas to enter the world of data processing Handle exceptions for writing reliable and usable code Cover manual and automatic aspects of testing for scientific programming Get to grips with parallel computing to increase computation speed Who this book is for: This book is for students with a mathematical background, university teachers designing modern courses in programming, data scientists, researchers, developers, and anyone who wants to perform scientific computation in Python.
Book Synopsis Python for Software Design by : Allen B. Downey
Download or read book Python for Software Design written by Allen B. Downey and published by Cambridge University Press. This book was released on 2009-03-09 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.
Book Synopsis Introduction to Computational Models with Python by : Jose M. Garrido
Download or read book Introduction to Computational Models with Python written by Jose M. Garrido and published by CRC Press. This book was released on 2015-08-28 with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Computational Models with Python explains how to implement computational models using the flexible and easy-to-use Python programming language. The book uses the Python programming language interpreter and several packages from the huge Python Library that improve the performance of numerical computing, such as the Numpy and Scipy m
Book Synopsis Handbook of Computer Programming with Python by : Dimitrios Xanthidis
Download or read book Handbook of Computer Programming with Python written by Dimitrios Xanthidis and published by CRC Press. This book was released on 2022-12-12 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides a hands-on experience based on the underlying topics, and assists students and faculty members in developing their algorithmic thought process and programs for given computational problems. It can also be used by professionals who possess the necessary theoretical and computational thinking background but are presently making their transition to Python. Key Features: Discusses concepts such as basic programming principles, OOP principles, database programming, GUI programming, application development, data analytics and visualization, statistical analysis, virtual reality, data structures and algorithms, machine learning, and deep learning Provides the code and the output for all the concepts discussed Includes a case study at the end of each chapter This handbook will benefit students of computer science, information systems, and information technology, or anyone who is involved in computer programming (entry-to-intermediate level), data analytics, HCI-GUI, and related disciplines.
Book Synopsis Programming in Two Semesters by : Quentin Charatan
Download or read book Programming in Two Semesters written by Quentin Charatan and published by Springer Nature. This book was released on 2022-10-01 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: This highly accessible textbook teaches programming from first principles. In common with many programming courses, it uses Python as the introductory programming language before going on to use Java as the vehicle for more advanced programming concepts. The first part, which teaches Python, covers fundamental programming concepts, such as data types and control structures and functions. It introduces more complex data types such as lists and dictionaries and also deals with file handling. It introduces object-oriented concepts and ends with a case study bringing together all the topics of the first semester. The second part uses Java to teach advanced concepts and centres around object-oriented programming, teaching key object-oriented concepts such as inheritance and polymorphism. The semester again ends with an advanced case study bringing together all the topics of the second semester. Topics and features: Assumes no prior knowledge, and makes the transition from Python to Java a smooth process Features numerous exercises and also an illustrative case study for each language Examines procedural and object-oriented methodologies, as well as design principles Covers such advanced topics as interfaces and lambda expressions, exceptions and Collections Includes a chapter on graphics programming in Python using Tkinter Introduces the latest Java technology for graphical interfaces, JavaFX Explains design concepts using UML notation Offering a gentle introduction to the field and assuming no prerequisite background, Programming in Two Semesters is the ideal companion to undergraduate modules in software development or programming. In addition, it will serve as a strong primer for professionals looking to strengthen their knowledge of programming with these languages.
Book Synopsis Introduction to Computation and Programming Using Python, second edition by : John V. Guttag
Download or read book Introduction to Computation and Programming Using Python, second edition written by John V. Guttag and published by MIT Press. This book was released on 2016-08-12 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including PyLab. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters. Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Book Synopsis Natural Computing with Python by : Zaccone Giancarlo
Download or read book Natural Computing with Python written by Zaccone Giancarlo and published by BPB Publications. This book was released on 2019-09-20 with total page 293 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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/
Book Synopsis Programming with Python by : Preeti Thareja
Download or read book Programming with Python written by Preeti Thareja and published by Rudra Publications. This book was released on with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Programming with Python makes the reader spend less time looking at a computer screen and more time thinking about fascinating problems to solve. Many basic programs were explained in the book to make the programming experience enjoyable and interesting. Along the way, the book also covers the fundamental concepts of program design and problem solving with computers. The book is written in a concise and clear manner that makes it easy for readers to understand its principles and is ideal for mass readers who want to start on with Python.
Book Synopsis Introduction to Computing and Programming in Python by : Mark J. Guzdial
Download or read book Introduction to Computing and Programming in Python written by Mark J. Guzdial and published by Pearson Higher Ed. This book was released on 2012-03-20 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introduction to Computing and Programming in Python, 3e, uses multimedia applications to motivate introductory computer science majors or non-majors. The book's hands-on approach shows how programs can be used to build multimedia computer science applications that include sound, graphics, music, pictures, and movies. The students learn a key set of computer science tools and topics, as well as programming skills; such as how to design and use algorithms, and practical software engineering methods. The book also includes optional coverage of HCI, as well as rudimentary data structures and databases using the user-friendly Python language for implementation. Authors Guzdial and Ericson also demonstrate how to communicate compatibly through networks and do concurrent programming.
Book Synopsis PRINCIPLES OF SOFT COMPUTING, 2ND ED (With CD ) by : S. N. Sivanandam
Download or read book PRINCIPLES OF SOFT COMPUTING, 2ND ED (With CD ) written by S. N. Sivanandam and published by John Wiley & Sons. This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Market_Desc: · B. Tech (UG) students ofü CSEü ITü ECE· College Libraries· Research Scholars· Operational Research· Management Sector Special Features: · Detailed explanation of soft computing concepts.· Study on various artificial neural network architecture.· Description on fuzzy logic techniques.· Introduction to genetic algorithm and its types for solving optimization problems.· Numerous artificial neural network, fuzzy logic and genetic algorithm problems.· Implementation of soft computing techniques using C and C++.· Simulated solutions for soft computing concepts using MATLAB package.· Application case studies on soft computing techniques on emerging fields.· Various hybrid soft computing techniques.New in this edition· Certain topics have been added such as:ü Fundamentals of Genetic Algorithmsü Genetic Modelingü Integration of Neural Networks, Fuzzy Logic, and Genetic Algorithms· A new chapter Hybrid Soft Computing Techniques has been added bringing the advantages of combining individual techniques.· 5 Sample Question Papers have been added at the end of the book. Accompanying CD contains · Power point presentations· Source Codes for Soft Computing Techniques in C· MATLAB Source Code Programs About The Book: In this book the basic concepts of soft computing are dealt in detail with the relevant information and knowledge available for understanding the computing process. The various neural network concepts are explained with examples, highlighting the difference between various architectures. Fuzzy logic techniques have been clearly dealt with suitable examples. Genetic algorithm operators and the various classifications have been discussed in lucid manner, so that a beginner can understand the concepts with minimal effort.The book can be used as a handbook as well as a guide for students of all engineering disciplines, soft computing research scholars, management sector, operational research area, computer applications and for various professionals who work in this area.
