Python For Scientific Computing And Artificial Intelligence PDF Download
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| Author | : Stephen Lynch |
| Publisher | : CRC Press |
| Total Pages | : 334 |
| Release | : 2023-06-15 |
| Genre | : Computers |
| ISBN | : 100088967X |
Download Python for Scientific Computing and Artificial Intelligence Book in PDF, ePub and Kindle
Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI). This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling. Features: No prior experience of programming is required. Online GitHub repository available with codes for readers to practice. Covers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computing. Full solutions to exercises are available as Jupyter notebooks on the Web. Support Material GitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/ Solutions to All Exercises: Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.html Section 2: Python for Scientific Computing: https://drstephenlynch.github.io/webpages/Solutions_Section_2.html Section 3: Artificial Intelligence: https://drstephenlynch.github.io/webpages/Solutions_Section_3.html
| Author | : CLAUS. FUHRER |
| Publisher | : |
| Total Pages | : 392 |
| Release | : 2021-07-23 |
| Genre | : |
| ISBN | : 9781838822323 |
Download Scientific Computing with Python - Second Edition Book in PDF, ePub and Kindle
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.
| Author | : Robert Johansson |
| Publisher | : Apress |
| Total Pages | : 709 |
| Release | : 2018-12-24 |
| Genre | : Computers |
| ISBN | : 1484242467 |
Download Numerical Python Book in PDF, ePub and Kindle
Leverage the numerical and mathematical modules in Python and its standard library as well as popular open source numerical Python packages like NumPy, SciPy, FiPy, matplotlib and more. This fully revised edition, updated with the latest details of each package and changes to Jupyter projects, demonstrates how to numerically compute solutions and mathematically model applications in big data, cloud computing, financial engineering, business management and more. Numerical Python, Second Edition, presents many brand-new case study examples of applications in data science and statistics using Python, along with extensions to many previous examples. Each of these demonstrates the power of Python for rapid development and exploratory computing due to its simple and high-level syntax and multiple options for data analysis. After reading this book, readers will be familiar with many computing techniques including array-based and symbolic computing, visualization and numerical file I/O, equation solving, optimization, interpolation and integration, and domain-specific computational problems, such as differential equation solving, data analysis, statistical modeling and machine learning. What You'll Learn Work with vectors and matrices using NumPy Plot and visualize data with Matplotlib Perform data analysis tasks with Pandas and SciPy Review statistical modeling and machine learning with statsmodels and scikit-learn Optimize Python code using Numba and Cython Who This Book Is For Developers who want to understand how to use Python and its related ecosystem for numerical computing.
| Author | : Claus Fuhrer |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 374 |
| Release | : 2021-07-30 |
| Genre | : Computers |
| ISBN | : 183882510X |
Download Scientific Computing with Python Book in PDF, ePub and Kindle
Leverage this example-packed, comprehensive guide for all your Python computational needs Key FeaturesLearn the first steps within Python to highly specialized conceptsExplore 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 learnUnderstand the building blocks of computational mathematics, linear algebra, and related Python objectsUse Matplotlib to create high-quality figures and graphics to draw and visualize resultsApply object-oriented programming (OOP) to scientific computing in PythonDiscover how to use pandas to enter the world of data processingHandle exceptions for writing reliable and usable codeCover manual and automatic aspects of testing for scientific programmingGet to grips with parallel computing to increase computation speedWho 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.
| Author | : Hans Petter Langtangen |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 743 |
| Release | : 2013-03-14 |
| Genre | : Computers |
| ISBN | : 3662054507 |
Download Python Scripting for Computational Science Book in PDF, ePub and Kindle
Scripting with Python makes you productive and increases the reliability of your scientific work. Here, the author teaches you how to develop tailored, flexible, and efficient working environments built from small programs (scripts) written in Python. The focus is on examples and applications of relevance to computational science: gluing existing applications and tools, e.g. for automating simulation, data analysis, and visualization; steering simulations and computational experiments; equipping programs with graphical user interfaces; making computational Web services; creating interactive interfaces with a Maple/Matlab-like syntax to numerical applications in C/C++ or Fortran; and building flexible object-oriented programming interfaces to existing C/C++ or Fortran libraries.
| Author | : Johnny Wei-Bing Lin |
| Publisher | : Cambridge University Press |
| Total Pages | : 767 |
| Release | : 2022-07-07 |
| Genre | : Computers |
| ISBN | : 1108701124 |
Download An Introduction to Python Programming for Scientists and Engineers Book in PDF, ePub and Kindle
Textbook that uses examples and Jupyter notebooks from across the sciences and engineering to teach Python programming.
| Author | : Hemant Kumar Mehta |
| Publisher | : Packt Publishing Ltd |
| Total Pages | : 301 |
| Release | : 2015-09-23 |
| Genre | : Computers |
| ISBN | : 1783288833 |
Download Mastering Python Scientific Computing Book in PDF, ePub and Kindle
A complete guide for Python programmers to master scientific computing using Python APIs and tools About This Book The basics of scientific computing to advanced concepts involving parallel and large scale computation are all covered. Most of the Python APIs and tools used in scientific computing are discussed in detail The concepts are discussed with suitable example programs Who This Book Is For If you are a Python programmer and want to get your hands on scientific computing, this book is for you. The book expects you to have had exposure to various concepts of Python programming. What You Will Learn Fundamentals and components of scientific computing Scientific computing data management Performing numerical computing using NumPy and SciPy Concepts and programming for symbolic computing using SymPy Using the plotting library matplotlib for data visualization Data analysis and visualization using Pandas, matplotlib, and IPython Performing parallel and high performance computing Real-life case studies and best practices of scientific computing In Detail In today's world, along with theoretical and experimental work, scientific computing has become an important part of scientific disciplines. Numerical calculations, simulations and computer modeling in this day and age form the vast majority of both experimental and theoretical papers. In the scientific method, replication and reproducibility are two important contributing factors. A complete and concrete scientific result should be reproducible and replicable. Python is suitable for scientific computing. A large community of users, plenty of help and documentation, a large collection of scientific libraries and environments, great performance, and good support makes Python a great choice for scientific computing. At present Python is among the top choices for developing scientific workflow and the book targets existing Python developers to master this domain using Python. The main things to learn in the book are the concept of scientific workflow, managing scientific workflow data and performing computation on this data using Python. The book discusses NumPy, SciPy, SymPy, matplotlib, Pandas and IPython with several example programs. Style and approach This book follows a hands-on approach to explain the complex concepts related to scientific computing. It details various APIs using appropriate examples.
| Author | : Jason Test |
| Publisher | : Independently Published |
| Total Pages | : 566 |
| Release | : 2021-03-17 |
| Genre | : |
| ISBN | : |
Download Quantum Computing with Python Book in PDF, ePub and Kindle
*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.
| Author | : Perry Xiao |
| Publisher | : John Wiley & Sons |
| Total Pages | : 724 |
| Release | : 2022-02-21 |
| Genre | : Computers |
| ISBN | : 1119820960 |
Download Artificial Intelligence Programming with Python Book in PDF, ePub and Kindle
A hands-on roadmap to using Python for artificial intelligence programming In Practical Artificial Intelligence Programming with Python: From Zero to Hero, veteran educator and photophysicist Dr. Perry Xiao delivers a thorough introduction to one of the most exciting areas of computer science in modern history. The book demystifies artificial intelligence and teaches readers its fundamentals from scratch in simple and plain language and with illustrative code examples. Divided into three parts, the author explains artificial intelligence generally, machine learning, and deep learning. It tackles a wide variety of useful topics, from classification and regression in machine learning to generative adversarial networks. He also includes: Fulsome introductions to MATLAB, Python, AI, machine learning, and deep learning Expansive discussions on supervised and unsupervised machine learning, as well as semi-supervised learning Practical AI and Python “cheat sheet” quick references This hands-on AI programming guide is perfect for anyone with a basic knowledge of programming—including familiarity with variables, arrays, loops, if-else statements, and file input and output—who seeks to understand foundational concepts in AI and AI development.
| Author | : Stephen Lynch |
| Publisher | : CRC Press |
| Total Pages | : 113 |
| Release | : 2024-06-11 |
| Genre | : Mathematics |
| ISBN | : 1040034756 |
Download A Simple Introduction to Python Book in PDF, ePub and Kindle
A Simple Introduction to Python is aimed at pre-university students and complete novices to programming. The whole book has been created using Jupyter notebooks. After introducing Python as a powerful calculator, simple programming constructs are covered, and the NumPy, MatPlotLib and SymPy modules (libraries) are introduced. Python is then used for Mathematics, Cryptography, Artificial Intelligence, Data Science and Object Oriented Programming. The reader is shown how to program using the integrated development environments: Python IDLE, Spyder, Jupyter notebooks, and through cloud computing with Google Colab. Features: No prior experience in programming is required. Demonstrates how to format Jupyter notebooks for publication on the Web. Full solutions to exercises are available as a Jupyter notebook on the Web. All Jupyter notebook solution files can be downloaded through GitHub. GitHub Repository of Data Files and a Jupyter Solution notebook: https://github.com/proflynch/A-Simple-Introduction-to-Python Jupyter Solution notebook web page: https://drstephenlynch.github.io/webpages/A-Simple-Introduction-to-Python-Solutions.html
