Search results for "handbook of computer programming with python"
Items we need to order for you
Handbook of Genetic Programming Applications
This contributed volume, written by leading international researchers, reviews the latest developments of genetic programming (GP) and its key applications in solving current real world problems, such as energy conversion and management, financial analysis, engineering modeling and design, and software engineering, to name a few. Inspired by natural evolution, the use of GP has expanded significantly in the last decade in almost every area of science and engineering. Exploring applications in a variety of fields, the information in this volume can help optimize computer programs throughout the sciences. Taking a hands-on approach, this book provides an invaluable reference to practitioners, providing the necessary details required for a successful application of GP and its branches to challenging problems ranging from drought prediction to trading volatility. It also demonstrates the evolution of GP through major developments in GP studies and applications. It is suitable for advanced students who wish to use relevant book chapters as a basis to pursue further research in these areas, as well as experienced practitioners looking to apply GP to new areas. The book also offers valuable supplementary material for design courses and computation in engineering.
R 6,611.61
R 916.00
Handbook of Mathematical Models with Python
Master the art of mathematical modeling through practical examples, use cases, and machine learning techniquesKey FeaturesGain a profound understanding of various mathematical models that can be integrated with machine learningLearn how to implement optimization algorithms to tune machine learning modelsBuild optimal solutions for practical use casesPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMathematical modeling is the art of transforming a business problem into a well-defined mathematical formulation. Its emphasis on interpretability is particularly crucial when deploying a model to support high-stake decisions in sensitive sectors like pharmaceuticals and healthcare.Through this book, you’ll gain a firm grasp of the foundational mathematics underpinning various machine learning algorithms. Equipped with this knowledge, you can modify algorithms to suit your business problem. Starting with the basic theory and concepts of mathematical modeling, you’ll explore an array of mathematical tools that will empower you to extract insights and understand the data better, which in turn will aid in making optimal, data-driven decisions. The book allows you to explore mathematical optimization and its wide range of applications, and concludes by highlighting the synergetic value derived from blending mathematical models with machine learning.Ultimately, you’ll be able to apply everything you’ve learned to choose the most fitting methodologies for the business problems you encounter.What you will learnUnderstand core concepts of mathematical models and their relevance in solving problemsExplore various approaches to modeling and learning using PythonWork with tested mathematical tools to gather meaningful insightsBlend mathematical modeling with machine learning to find optimal solutions to business problemsOptimize ML models built with business data, apply them to understand their impact on the business, and address critical questionsApply mathematical optimization for data-scarce problems where the objective and constraints are knownWho this book is forIf you are a budding data scientist seeking to augment your journey with mathematics, this book is for you. Researchers and R&D scientists will also be able to harness the concepts covered to their full potential. To make the best use of this book, a background in linear algebra, differential equations, basics of statistics, data types, data structures, and numerical algorithms will be useful.
R 1,693.00
R 1,840.10
C Programming: The Essentials for Engineers and Scientists
This text teaches the essentials of C programming, concentrating on what readers need to know in order to produce stand-alone programs and so solve typical scientific and engineering problems. It is a learning-by-doing book, with many examples and exercises, and lays a foundation of scientific programming concepts and techniques that will prove valuable for those who might eventually move on to another language. Written for undergraduates who are familiar with computers and typical applications but are new to programming.
R 2,800.67
Programming with Specifications
Topics • what this book is about, • its intended audience, • what the reader ought to know, • how the book is organized, • acknowledgements. Specifications express information about a program that is not normally part of the program, and often cannot be expressed in a programming lan guage. In the past, the word "specification" has sometimes been used to refer to somewhat vague documentation written in English. But today it indicates a precise statement, written in a machine processable language, about the purpose and behavior of a program. Specifications are written in languages that are just as precise as programming languages, but have additional capabilities that increase their power of expression. The termi nology formal specification is sometimes used to emphasize the modern meaning. For us, all specifications are formal. The use of specifications as an integral part of a program opens up a whole new area of programming - progmmming with specifications. This book describes how to use specifications in the process of building programs, debugging them, and interfacing them with other programs. It deals with a new trend in programming - the evolution of specification languages from the current generation of programming languages. And it describes new strategies and styles of programming that utilize specifications. The trend is just beginning, and the reader, having finished this book, will viii Preface certainly see that there is much yet to be done and to be discovered about programming with specifications.
R 2,196.21
OpenCV: Computer Vision Projects with Python
Get savvy with OpenCV and actualize cool computer vision applicationsAbout This Book* Use OpenCV's Python bindings to capture video, manipulate images, and track objects* Learn about the different functions of OpenCV and their actual implementations.* Develop a series of intermediate to advanced projects using OpenCV and PythonWho This Book Is ForThis learning path is for someone who has a working knowledge of Python and wants to try out OpenCV. This Learning Path will take you from a beginner to an expert in computer vision applications using OpenCV. OpenCV's application are humongous and this Learning Path is the best resource to get yourself acquainted thoroughly with OpenCV.What You Will Learn* Install OpenCV and related software such as Python, NumPy, SciPy, OpenNI, and SensorKinect - all on Windows, Mac or Ubuntu* Apply "curves" and other color transformations to simulate the look of old photos, movies, or video games* Apply geometric transformations to images, perform image filtering, and convert an image into a cartoon-like image* Recognize hand gestures in real time and perform hand-shape analysis based on the output of a Microsoft Kinect sensor* Reconstruct a 3D real-world scene from 2D camera motion and common camera reprojection techniques* Detect and recognize street signs using a cascade classifier and support vector machines (SVMs)* Identify emotional expressions in human faces using convolutional neural networks (CNNs) and SVMs* Strengthen your OpenCV2 skills and learn how to use new OpenCV3 featuresIn DetailOpenCV is a state-of-art computer vision library that allows a great variety of image and video processing operations. OpenCV for Python enables us to run computer vision algorithms in real time. This learning path proposes to teach the following topics. First, we will learn how to get started with OpenCV and OpenCV3's Python API, and develop a computer vision application that tracks body parts. Then, we will build amazing intermediate-level computer vision applications such as making an object disappear from an image, identifying different shapes, reconstructing a 3D map from images , and building an augmented reality application, Finally, we'll move to more advanced projects such as hand gesture recognition, tracking visually salient objects, as well as recognizing traffic signs and emotions on faces using support vector machines and multi-layer perceptrons respectively. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products:* OpenCV Computer Vision with Python by Joseph Howse * OpenCV with Python By Example by Prateek Joshi* OpenCV with Python Blueprints by Michael BeyelerStyle and approachThis course aims to create a smooth learning path that will teach you how to get started with will learn how to get started with OpenCV and OpenCV 3's Python API, and develop superb computer vision applications. Through this
R 2,605.00
Mastering OpenCV 4 with Python
Create advanced applications with Python and OpenCV, exploring the potential of facial recognition, machine learning, deep learning, web computing and augmented reality.Key FeaturesDevelop your computer vision skills by mastering algorithms in Open Source Computer Vision 4 (OpenCV 4) and PythonApply machine learning and deep learning techniques with TensorFlow and KerasDiscover the modern design patterns you should avoid when developing efficient computer vision applicationsBook DescriptionOpenCV is considered to be one of the best open source computer vision and machine learning software libraries. It helps developers build complete projects in relation to image processing, motion detection, or image segmentation, among many others. OpenCV for Python enables you to run computer vision algorithms smoothly in real time, combining the best of the OpenCV C++ API and the Python language.In this book, you'll get started by setting up OpenCV and delving into the key concepts of computer vision. You'll then proceed to study more advanced concepts and discover the full potential of OpenCV. The book will also introduce you to the creation of advanced applications using Python and OpenCV, enabling you to develop applications that include facial recognition, target tracking, or augmented reality. Next, you'll learn machine learning techniques and concepts, understand how to apply them in real-world examples, and also explore their benefits, including real-time data production and faster data processing. You'll also discover how to translate the functionality provided by OpenCV into optimized application code projects using Python bindings. Toward the concluding chapters, you'll explore the application of artificial intelligence and deep learning techniques using the popular Python libraries TensorFlow, and Keras.By the end of this book, you'll be able to develop advanced computer vision applications to meet your customers' demands.What you will learnHandle files and images, and explore various image processing techniquesExplore image transformations, including translation, resizing, and croppingGain insights into building histogramsBrush up on contour detection, filtering, and drawingWork with Augmented Reality to build marker-based and markerless applicationsWork with the main machine learning algorithms in OpenCVExplore the deep learning Python libraries and OpenCV deep learning capabilitiesCreate computer vision and deep learning web applicationsWho this book is forThis book is designed for computer vision developers, engineers, and researchers who want to develop modern computer vision applications. Basic experience of OpenCV and Python programming is a must.
R 1,661.00
Introduction to Programming with Fortran
This fourth Edition presents new examples on submodules, derived type i/o, object oriented programming, abstract interfaces and procedure pointers, C interop, sorting and searching, statistics and converting to more modern versions of Fortran.Key FeaturesHighlights the core language features of modern Fortran including data typing, array processing, control structures, functions, subroutines, modules and submodules, user defined types, pointers, operator overloading, generic programming, parallel programming, abstract interfaces, procedure pointersPinpoints common problems that occur when programmingIllustrates the use of several compilersIntroduction to Programming with Fortran has been written for the complete beginner with little or no programming background as well as existing Fortran programmers and those with programming experience in other languages
R 4,002.52
Multi-Platform Graphics Programming with Kivy
Modern science requires computer graphics models to provide realistic visual renderings. Learning the appropriate programming tools for 2D and 3D modeling doesn’t have to be so difficult. This book reviews the best programming tools to achieve this and explains how to apply them to mobile platforms like Android. Multi-Platform Graphics Programming with Kivy provides a straightforward introductory approach for designing 2D, 3D, and stereoscopic applications, using analytical equations from vector algebra. Throughout the book you’ll look closely at this approach and develop scenes in Kivy, taking advantage of powerful mathematical functions for arrays by NumPy for Python. Unbuntu is used to develop the programs, which allows you to easily convert to Android platform. Each chapter contains step-by-step descriptions on each subject and provides complete program listings.What You’ll LearnWork with Kivy, a modern, powerful multi-platform graphics systemConvert and run programs on Android devicesProgram, fill faces, and rotate 2D and 3D polygonsApply the concepts of 2D and 3D applicationsDevelop stereoscopic scenesReview a straightforward introduction to 2D, 3D, and stereoscopic graphics applicationsUse simple analytical equations from vector algebraWho This Book Is ForThe primary audience is students and researchers in graphics programming with experience in analytical equations.
R 1,254.00
Speed Up Your Python with Rust
Discover how to inject your code with highly performant Rust features to develop fast and memory-safe applicationsKey FeaturesLearn to implement Rust in a Python system without altering the entire systemWrite safe and efficient Rust code as a Python developer by understanding the essential features of RustBuild Python extensions in Rust by using Python NumPy modules in your Rust codeBook DescriptionPython has made software development easier, but it falls short in several areas including memory management that lead to poor performance and security. Rust, on the other hand, provides memory safety without using a garbage collector, which means that with its low memory footprint, you can build high-performant and secure apps relatively easily. However, rewriting everything in Rust can be expensive and risky as there might not be package support in Rust for the problem being solved. This is where Python bindings and pip come in.This book will help you, as a Python developer, to start using Rust in your Python projects without having to manage a separate Rust server or application. Seeing as you'll already understand concepts like functions and loops, this book covers the quirks of Rust such as memory management to code Rust in a productive and structured manner. You'll explore the PyO3 crate to fuse Rust code with Python, learn how to package your fused Rust code in a pip package, and then deploy a Python Flask application in Docker that uses a private Rust pip module. Finally, you'll get to grips with advanced Rust binding topics such as inspecting Python objects and modules in Rust.By the end of this Rust book, you'll be able to develop safe and high-performant applications with better concurrency support.What you will learnExplore the quirks of the Rust programming language that a Python developer needs to understand to code in RustUnderstand the trade-offs for multiprocessing and thread safety to write concurrent codeBuild and manage a software project with cargo and cratesFuse Rust code with Python so that Python can import and run Rust codeDeploy a Python Flask application in Docker that utilizes a private Rust pip moduleInspect and create your own Python objects in RustWho this book is forThis book is for Python developers who want to speed up their Python code with Rust and implement Rust in a Python system without altering the entire system. You'll be able to learn about all topics relating to Rust programming. Basic knowledge of Python is required to get the most out of this book.
R 1,498.00
R 1,282.00
Natural Language Processing with Python Quick Start Guide
Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learningKey FeaturesA no-math, code-driven programmer’s guide to text processing and NLPGet state of the art results with modern tooling across linguistics, text vectors and machine learningFundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorchBook DescriptionNLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP.The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications.We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn.We conclude by deploying these models as REST APIs with Flask.By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges.What you will learnUnderstand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpusWork with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clusteringDeep Learning in NLP using PyTorch with a code-driven introduction to PyTorchUsing an NLP project management Framework for estimating timelines and organizing your project into stagesHack and build a simple chatbot application in 30 minutesDeploy an NLP or machine learning application using Flask as RESTFUL APIsWho this book is forProgrammers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.
R 1,140.00
Programming with TensorFlow
This practical book provides an end-to-end guide to TensorFlow, the leading open source software library that helps you build and train neural networks for deep learning, Natural Language Processing (NLP), speech recognition, and general predictive analytics. The book provides a hands-on approach to TensorFlow fundamentals for a broad technical audience—from data scientists and engineers to students and researchers. The authors begin by working through some basic examples in TensorFlow before diving deeper into topics such as CNN, RNN, LSTM, and GNN. The book is written for those who want to build powerful, robust, and accurate predictive models with the power of TensorFlow, combined with other open source Python libraries. The authors demonstrate TensorFlow projects on Single Board Computers (SBCs).
R 3,179.86
R 550.00
R 482.00
R 367.00
R 641.00
R 1,248.14
R 763.00
Foundation Dynamic Web Pages with Python
Discover the concepts of creating dynamic web pages (HTML) with Python. This book reviews several methods available to serve up dynamic HTML including CGI, SSI, Django, and Flask. You will start by covering HTML pages and CSS in general and then move on to creating pages via CGI. It is easy to use and can serve as a foundation for the more advanced services available for launching dynamic web pages. Next you'll explore the SSI (Server Side Interface) method. This is a slightly more advanced interface included in mots web servers that adds functionality to modify static HTML pages to add such things as the current date or time, include additional HTML, and other features to a static web page before it is delivered to the user. The book also covers some of the key the Django module features, which must be added to the web server. These features include creating dynamic web pages and calling a database to provide additional information to the web page. Lastly you will explore the Flask module. While it has limited functionality on its own, it provides a very flexible environment to create a self designed system for delivery of dynamic web pages.By the time you finish this book, you will be able to choose the appropriate methodology for delivering dynamic information using fast HTML creation services.What You'll LearnUse HTML pages and CSS together to control the style of your web site.Install and configure SSI, Django, and Flask for Apache.Create dynamic web pages using CGI and creating a library of partial HTML pages to use in this task.Build dynamic web pages using SSI and auxiliary Python programs to enhance the SSI functionality.Develop dynamic web pages using Django.Who This Book Is ForSoftware Developers with basic Python programming skills interested in learning Web Development
R 1,026.00
Hands-On Simulation Modeling with Python
Learn to construct state-of-the-art simulation models with Python and enhance your simulation modelling skills, as well as create and analyze digital prototypes of physical models with easeKey FeaturesUnderstand various statistical and physical simulations to improve systems using PythonLearn to create the numerical prototype of a real model using hands-on examplesEvaluate performance and output results based on how the prototype would work in the real worldBook DescriptionSimulation modelling is an exploration method that aims to imitate physical systems in a virtual environment and retrieve useful statistical inferences from it. The ability to analyze the model as it runs sets simulation modelling apart from other methods used in conventional analyses. This book is your comprehensive and hands-on guide to understanding various computational statistical simulations using Python. The book begins by helping you get familiarized with the fundamental concepts of simulation modelling, that’ll enable you to understand the various methods and techniques needed to explore complex topics. Data scientists working with simulation models will be able to put their knowledge to work with this practical guide. As you advance, you’ll dive deep into numerical simulation algorithms, including an overview of relevant applications, with the help of real-world use cases and practical examples. You'll also find out how to use Python to develop simulation models and how to use several Python packages. Finally, you’ll get to grips with various numerical simulation algorithms and concepts, such as Markov Decision Processes, Monte Carlo methods, and bootstrapping techniques.By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.What you will learnGet to grips with the concept of randomness and the data generation processDelve into resampling methodsDiscover how to work with Monte Carlo simulationsUtilize simulations to improve or optimize systemsFind out how to run efficient simulations to analyze real-world systemsUnderstand how to simulate random walks using Markov chainsWho this book is forThis book is for data scientists, simulation engineers, and anyone who is already familiar with the basic computational methods and wants to implement various simulation techniques such as Monte-Carlo methods and statistical simulation using Python.
R 1,693.00
R 518.00
R 855.00
AI and ML for Coders in Pytorch
Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed.From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently.Gain the confidence to apply AI without needing advanced math or theory expertiseDiscover how to build AI models for computer vision, NLP, and sequence modeling with PyTorchLearn generative AI techniques with Hugging Face Diffusers and Transformers
R 1,824.00
Cambridge IGCSE™ and O Level Computer Science Programming Book for Microsoft® Visual Basic with Digital Access (2 Years)
This series supports learners through the Cambridge IGCSE™ and O Level Computer Science syllabuses (0478/0984/2210). Develop skills and confidence with our programming book for Microsoft® Visual Basic. Created to support students undertaking the Cambridge IGCSE™ and O Level Computer Science syllabuses, this resource provides tailored support when programming with Microsoft® Visual Basic. A three-tiered approach to programming tasks across the book provides scaffolded support for students of all levels of understanding. Answers are accessible in the 'Solutions' chapter in the digital part of the resource, enabling students to practise their programming skills in class or at home.
R 1,054.00
Foundations of Crystallography with Computer Applications
The Third Edition of Foundations of Crystallography with Computer Applications is a textbook for undergraduate and graduate students studying the solid state in chemistry, physics, materials science, geological sciences, and engineering. It takes a straightforward, logical approach to explaining how atoms are arranged in crystals and how crystal systems are related to each other. New to this edition is the inclusion of interactive starter programs in Python, which allow the students to focus on concepts and not treat crystallographic programs as ‘black boxes.’ Since many students have trouble visualizing three dimensional constructions, this book begins with detailed discussions in two dimensions leading up to the three-dimensional understanding. The first 7 chapters introduce the fundamental principles; chapter 8 suggests student projects, and the final 7 chapters give detailed examples of the 7 crystal systems. Key features: Uses Python, the leading open-source scientific language, with libraries including Numpy for matrix manipulations, Matplotlib for graphics and Mplot3d for interactive 3-D modelling. Provides a gentle introduction to Python with Jupyter Notebooks, which combine interactive code and formatted documentation. Color codes both point group and space group diagrams using a new scheme devised by the author to emphasize the change of handedness of the symmetry operations and their consequences. Suggests student projects with data that can be found in the free Teaching Subset of the Cambridge Structural Database, the American Mineralogist Crystal Structure Database, and others. This book’s thorough but accessible style gives students a strong foundation in the subject. Over one thousand students have successfully used this book at Virginia Tech, and many more will continue to benefit from this new edition.
R 3,700.00
R 1,008.00
Beginning Ethereum Smart Contracts Programming
Use this book to write an Ethereum blockchain smart contract, test it, deploy it, and create a web application to interact with your smart contract. This new edition has been expanded and updated to cover web3.js APIs, additional Consensus Protocols, non-Fungible Tokens (NFTs), developing NFT tokens using ERC-721, and more!Beginning Ethereum Smart Contracts Programming, second edition is your fastest and most efficient means of getting started if you are unsure where to begin and how to connect to the Ethereum blockchain. The book begins with a foundational discussion of blockchain and the motivation behind it. From there, you will get up close and personal with the Ethereum blockchain, learning how to use an Ethereum client (geth) to create a private Ethereum blockchain to perform transactions such as sending Ethers to another account on another node. You will learn about smart contracts without having to wade through tons of documentation. Author Lee’s “learn-by-doing” approach will allow you to be productive and feel confident in your ability in no time. The last part of this book covers tokens, a topic that has taken the cryptocurrency market by storm.Sample code in Python, Solidity, and JavaScript is provided in the book and online.What You'll LearnUnderstand the basic premise of blockchain and “record keeping” in a peer-to-peer networkExperience blockchain in action by creating your own blockchain using PythonKnow the foundation of smart contracts programming and how to deploy and test smart contractsWork on a case study to illustrate the use of blockchainBe familiar with tokens, and how to create and launch your own ICO digital tokenWrite smart contracts that transact using tokensWho This Book Is ForThose who want to get started quickly with Ethereum smart contracts programming. Basic programming knowledge and an understanding of Python or JavaScript is recommended.
R 1,600.18
Programming with Data
Here is a thorough and authoritative guide to the latest version of the S language and its programming environment. Programming With Data describes a new and greatly extended version of S, written by the chief designer of the language itself. It is a guide to the complete programming process, starting from simple, interactive use, and continuing through ambitious software projects. The focus is on the needs of the programmer/user, with the aim of turning ideas into software, quickly and faithfully. The new version of S provides a powerful class/method structure, new techniques to deal with large objects, extended interfaces to other languages and files, object-based documentation compatible with HTML, and powerful new interactive programming techniques. This version of S underlies the S-Plus system, versions 5.0 and higher.
R 1,586.80
R 531.00
R 1,598.14
Handbook of Logic in Artificial Intelligence and Logic Programming: Volume 1: Logic Foundations
Logic is now widely recognized to be one of the foundational disciplines of computing and has found applications in virtually all aspects of the subject, from software engineering and hardware to programming languages and artificial intelligence. This Handbook has been created in response to the growing need for an in-depth survey of the applications of logic in AI and computer science.The Handbook of Logic in Artificial Intelligence and Logic Programming will be published in five volumes. Each volume provides a combination of authoritative exposition, comprehensive survey, and fundamental research exploring the underlying unifying themes in the various areas. this first volume presents the logical foundations and deduction methodologies extensively used in AI.
R 17,513.62
Cambridge IGCSE™ and O Level Computer Science Programming Book for Java with Digital Access (2 Years)
This series supports learners through the Cambridge IGCSE™ and O Level Computer Science syllabuses (0478/0984/2210). Develop skills and confidence with our new programming book for Java. Created in response to the addition of Java as a programming language in the Cambridge IGCSE™ and O Level Computer Science syllabuses, this resource provides tailored support for students programming with Java. A three-tiered approach to programming tasks across the book provides scaffolded support for students of all levels of understanding. Answers are accessible in the 'Solutions' chapter in the digital part of the resource, enabling students to practise their programming skills in class or at home.
R 1,054.00
