Search results for "Master Multi-Paradigm Python Programming"
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R 397.00
R 611.00
Hands-On APIs for AI and Data Science
To succeed in AI and data science, you must first master APIs. API skills are essential for AI and data science success. With this practical book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit.Part 1 takes you step-by-step through coding projects to build APIs using Python and FastAPI and deploy them in the cloud. Part 2 teaches you to consume APIs in a data science project using industry-standard tools. And in Part 3, you'll use ChatGPT, the LangChain framework, and other tools to access your APIs with generative AI and large language models (LLMs).As you complete the chapters in the book, you'll be creating a professional online portfolio demonstrating your new skill with APIs, AI, and data science.You'll learn how to:Design APIs that data scientists and AIs loveDevelop APIs using Python and FastAPIDeploy APIs using multiple cloud providersCreate data science projects such as visualizations and models using APIs as a data sourceAccess APIs using generative AI and LLMsAuthor Ryan Day is a data scientist in the financial services industry and an open source developer.
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Concise Introduction to Programming in Python
A Concise Introduction to Programming in Python, Second Edition provides a hands-on and accessible introduction to writing software in Python, with no prior programming experience required.The Second Edition was thoroughly reorganized and rewritten based on classroom experience to incorporate: A spiral approach, starting with turtle graphics, and then revisiting concepts in greater depth using numeric, textual, and image data Clear, concise explanations written for beginning students, emphasizing core principles A variety of accessible examples, focusing on key concepts Diagrams to help visualize new concepts New sections on recursion and exception handling, as well as an earlier introduction of lists, based on instructor feedbackThe text offers sections designed for approximately one class period each, and proceeds gradually from procedural to object-oriented design. Examples, exercises, and projects are included from diverse application domains, including finance, biology, image processing, and textual analysis. It also includes a brief "How-To" sections that introduce optional topics students may be interested in exploring.The text is written to be read, making it a good fit in flipped classrooms. Designed for either classroom use or self-study, all example programs and solutions to odd-numbered exercises (except for projects) are available at: http://www.central.edu/go/conciseintro/.
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Mastering Python Forensics
Master the art of digital forensics and analysis with PythonAbout This Book• Learn to perform forensic analysis and investigations with the help of Python, and gain an advanced understanding of the various Python libraries and frameworks• Analyze Python scripts to extract metadata and investigate forensic artifacts• The writers, Dr. Michael Spreitzenbarth and Dr. Johann Uhrmann, have used their experience to craft this hands-on guide to using Python for forensic analysis and investigationsWho This Book Is ForIf you are a network security professional or forensics analyst who wants to gain a deeper understanding of performing forensic analysis with Python, then this book is for you. Some Python experience would be helpful.What You Will Learn• Explore the forensic analysis of different platforms such as Windows, Android, and vSphere• Semi-automatically reconstruct major parts of the system activity and time-line• Leverage Python ctypes for protocol decoding• Examine artifacts from mobile, Skype, and browsers• Discover how to utilize Python to improve the focus of your analysis• Investigate in volatile memory with the help of volatility on the Android and Linux platformsIn DetailDigital forensic analysis is the process of examining and extracting data digitally and examining it. Python has the combination of power, expressiveness, and ease of use that makes it an essential complementary tool to the traditional, off-the-shelf digital forensic tools.This book will teach you how to perform forensic analysis and investigations by exploring the capabilities of various Python libraries.The book starts by explaining the building blocks of the Python programming language, especially ctypes in-depth, along with how to automate typical tasks in file system analysis, common correlation tasks to discover anomalies, as well as templates for investigations. Next, we'll show you cryptographic algorithms that can be used during forensic investigations to check for known files or to compare suspicious files with online services such as VirusTotal or Mobile-Sandbox.Moving on, you'll learn how to sniff on the network, generate and analyze network flows, and perform log correlation with the help of Python scripts and tools. You'll get to know about the concepts of virtualization and how virtualization influences IT forensics, and you'll discover how to perform forensic analysis of a jailbroken/rooted mobile device that is based on iOS or Android.Finally, the book teaches you how to analyze volatile memory and search for known malware samples based on YARA rules.Style and approachThis easy-to-follow guide will demonstrate forensic analysis techniques by showing you how to solve real-word-scenarios step by step.
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R 245.00
Python GUI Programming - A Complete Reference Guide
Explore Python’s GUI frameworks and create visually stunning and feature-rich applicationsKey FeaturesIntegrate stunning data visualizations using Tkinter Canvas and MatplotlibUnderstand the basics of 2D and 3D animation in GUI applicationsExplore PyQt’s powerful features to easily design and customize your GUI applicationsBook DescriptionA responsive graphical user interface (GUI) helps you interact with your application, improves user experience, and enhances the efficiency of your applications. With Python, you’ll have access to elaborate GUI frameworks that you can use to build interactive GUIs that stand apart from the rest.This Learning Path begins by introducing you to Tkinter and PyQt, before guiding you through the application development process. As you expand your GUI by adding more widgets, you'll work with networks, databases, and graphical libraries that enhance its functionality. You'll also learn how to connect to external databases and network resources, test your code, and maximize performance using asynchronous programming. In later chapters, you'll understand how to use the cross-platform features of Tkinter and Qt5 to maintain compatibility across platforms. You’ll be able to mimic the platform-native look and feel, and build executables for deployment across popular computing platforms.By the end of this Learning Path, you'll have the skills and confidence to design and build high-end GUI applications that can solve real-world problems.This Learning Path includes content from the following Packt products:Python GUI Programming with Tkinter by Alan D. MooreQt5 Python GUI Programming Cookbook by B. M. HarwaniWhat you will learnVisualize graphs in real time with Tkinter’s animation capabilitiesUse PostgreSQL authentication to ensure data security for your applicationWrite unit tests to avoid regression when updating codeHandle different signals generated on mouse clicks using QSpinBox and slidersEmploy network concepts, internet browsing, and Google Maps in UIUse graphics rendering to implement animations in your GUIWho this book is forIf you’re an intermediate Python programmer looking to enhance your coding skills by writing powerful GUIs in Python using PyQT and Tkinter, this is an ideal Learning Path for you. A strong understanding of the Python language is a must to grasp the concepts explained in this book.
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Multicriteria Portfolio Construction with Python
This book covers topics in portfolio management and multicriteria decision analysis (MCDA), presenting a transparent and unified methodology for the portfolio construction process. The most important feature of the book includes the proposed methodological framework that integrates two individual subsystems, the portfolio selection subsystem and the portfolio optimization subsystem. An additional highlight of the book includes the detailed, step-by-step implementation of the proposed multicriteria algorithms in Python. The implementation is presented in detail; each step is elaborately described, from the input of the data to the extraction of the results. Algorithms are organized into small cells of code, accompanied by targeted remarks and comments, in order to help the reader to fully understand their mechanics. Readers are provided with a link to access the source code through GitHub.This Work may also be considered as a reference which presents the state-of-art research on portfolio construction with multiple and complex investment objectives and constraints. The book consists of eight chapters. A brief introduction is provided in Chapter 1. The fundamental issues of modern portfolio theory are discussed in Chapter 2. In Chapter 3, the various multicriteria decision aid methods, either discrete or continuous, are concisely described. In Chapter 4, a comprehensive review of the published literature in the field of multicriteria portfolio management is considered. In Chapter 5, an integrated and original multicriteria portfolio construction methodology is developed. Chapter 6 presents the web-based information system, in which the suggested methodological framework has been implemented. In Chapter 7, the experimental application of the proposed methodology is discussed and in Chapter 8, the authors provide overall conclusions.The readership of the book aims to be a diverse group, including fund managers, risk managers, investment advisors, bankers, private investors, analytics scientists, operations researchers scientists, and computer engineers, to name just several. Portions of the book may be used as instructional for either advanced undergraduate or post-graduate courses in investment analysis, portfolio engineering, decision science, computer science, or financial engineering.
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Introduction to Python and Computer Programming
This book introduces Python programming language and fundamental concepts in algorithms and computing. Its target audience includes students and engineers with little or no background in programming, who need to master a practical programming language and learn the basic thinking in computer science/programming. The main contents come from lecture notes for engineering students from all disciplines, and has received high ratings. Its materials and ordering have been adjusted repeatedly according to classroom reception. Compared to alternative textbooks in the market, this book introduces the underlying Python implementation of number, string, list, tuple, dict, function, class, instance and module objects in a consistent and easy-to-understand way, making assignment, function definition, function call, mutability and binding environments understandable inside-out. By giving the abstraction of implementation mechanisms, this book builds a solid understanding of the Python programming language.
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Object-Oriented and Mixed Programming Paradigms
The area of computer graphics is characterized by rapid evolution. New techniques in hardware and software developments, e. g. , new rendering methods, have led to new ap plications and broader acceptance of graphics in fields such as scientific visualization, multi-media applications, computer aided design, and virtual reality systems. The evolving functionality and the growing complexity of graphics algorithms and sys tems make it more difficult for the application programmer to take full advantage of these systems. Conventional programming methods are no longer suited to manage the increasing complexity, so new programming paradigms and system architectures are re quired. One important step in this direction is the introduction and use of object-oriented methods. Intuition teils us that visible graphical entities are objects, and experience has indeed shown that object-oriented software techniques are quite useful for graphics. The expressiveness of object-oriented languages compared to pure procedurallanguages gives the graphics application programmer much better support when transforming his mental intentions into computer code. Moreover, object-oriented software development is a, weil founded technology, allowing software to be built from reusable and extensible compo nents. This book contains selected, reviewed and thoroughly revised vers ions of papers submit ted to and presented at the Fourth Eurographies Workshops on Object-Oriented Graphics, held on May 9-11, 1994 in Sintra, Portugal.
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Logic Programming Paradigm
This exciting new text reveals both the evolution of this programming paradigm since its inception and the impressively broad scope of current research in the field. The contributors to this book are all leading world experts in Logic Programming, and they deal with both theoretical and practical issues. They address such diverse topics as: computational molecular biology, machine learning, mobile computing, multi-agent systems, planning, numerical computing and dynamical systems, database systems, an alternative to the "formulas as types" approach, program semantics and analysis, and natural language processing. XXXXXXX Neuer Text Logic Programming was founded 25 years ago. This exciting book reveals both the evolution of this programming paradigm and its impressively broad scope of current research. The contributions by leading computer scientists deal with both theoretical and practical issues. They address diverse topics such as: computational molecular biology, machine learning, mobile computing, multi-agent systems, numerical computing and dynamical systems, database systems, program semantics, natural language processing, and promising future directions.
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AI Agents and Applications
Your AI prototype works once, then breaks. Ready for production stability? Tired of hallucinations ruining demos and stakeholder trust? Need agent workflows that survive real-world edge cases? Wondering how early adopters ship multi-agent systems today? Stop guessing, start delivering value with proven, open-source tools. Build confident, future-proof AI products your users will rely on. Prompt and context engineering: Produce accurate, hallucination-free outputs your business can trust. Advanced RAG techniques: Summarize documents, power semantic search, and answer questions with verifiable sources. LangGraph agent workflows: Orchestrate multi-step processes for complex, real-world tasks. MCP tool integration: Plug, compose, and reuse capabilities across projects for faster releases. End-to-end code examples: Copy, adapt, and deploy without time-consuming trial and error. AI Agents and Applications with LangChain, LangGraph, and MCP by seasoned developer Roberto Infante delivers a pragmatic, code-first roadmap in a clear softcover format. Infante shows exactly how to move from idea to production-grade AI. Each chapter builds a working solution, starting with solid prompt engineering, layering in advanced RAG, then evolving into structured agents and multi-agent systems. Visual explanations, annotated Python listings, and architecture diagrams speed learning and reduce guesswork. By the final page you will confidently design, test, and deploy LLM applications that delight users and impress stakeholders. The tools and patterns scale with your data, your team, and tomorrow’s models. Ideal for Python developers who grasp LLM basics and crave real production wins. Perfect for engineers, data scientists, and tech leads modernizing products with generative AI.
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Numerical Methods in Physics with Python
Bringing together idiomatic Python programming, foundational numerical methods, and physics applications, this is an ideal standalone textbook for courses on computational physics. All the frequently used numerical methods in physics are explained, including foundational techniques and hidden gems on topics such as linear algebra, differential equations, root-finding, interpolation, and integration. The second edition of this introductory book features several new codes and 140 new problems (many on physics applications), as well as new sections on the singular-value decomposition, derivative-free optimization, Bayesian linear regression, neural networks, and partial differential equations. The last section in each chapter is an in-depth project, tackling physics problems that cannot be solved without the use of a computer. Written primarily for students studying computational physics, this textbook brings the non-specialist quickly up to speed with Python before looking in detail at the numerical methods often used in the subject.
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Absolute Beginner's Guide to Python Programming
Written as an illustrated, step-by-step guide, this book will introduce you to Python with examples using the latest version of the language. You'll begin by learning to set up your Python environment. The next few chapters cover the basics of Python such as language classifications, Python language syntax, and how to write a program. Next, you will learn how to work with variables, basic data types, arithmetic, companion, and Boolean operators, followed by lab exercises. Further, the book covers flow control, using functions, and exception handling, as well as the principles of object-oriented programming and building an interface design. The last section explains how to develop a game by installing PyGame and how to use basic animation, and concludes with coverage of Python web development with web servers and Python web frameworks. The Absolute Beginners Guide to Python Programming will give you the tools, confidence, and inspiration to start writing Python programs. If you are a programmer, developer, or a student, or someone who wants to learn on their own, this book is for you.What You Will LearnGain an understanding of computer programming Understand different data and data typesWork with Classes and OOPBuild interfaces, simple games, and web development with PythonWho This Book Is ForSoftware programmers, developers or students, or anyone who wants to learn Python programming on their own.
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Mastering Functional Programming
Learn how functional programming can help you in deploying web servers and working with databases in a declarative and pure wayKey FeaturesLearn functional programming from scratchProgram applications with side effects in a pure wayGain expertise in working with array tools for functional programmingBook DescriptionIn large projects, it can get difficult keeping track of all the interdependencies of the code base and how its state changes at runtime. Functional Programming helps us solve these problems. It is a paradigm specifically designed to deal with the complexity of software development. This book will show you how the right abstractions can reduce complexity and make your code easy to read and understand.Mastering Functional Programming begins by touching upon the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to more advanced concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You will also explore some of the more advanced patterns in the world of functional programming, such as monad transformers and Tagless Final. In the concluding chapters, you will be introduced to the actor model, implement it in modern functional languages, and explore the subject of parallel programming.By the end of the book, you will have mastered the concepts entailing functional programming along with object-oriented programming (OOP) to build robust applications.What you will learnWrite reliable and scalable software based on solid foundationsExplore the cutting edge of computer science researchEffectively solve complex architectural problems in a robust wayAvoid unwanted outcomes such as errors or delays and focus on business logicWrite parallel programs in a functional style using the actor modelUse functional data structures and collections in your day-to-day workWho this book is forIf you are from an imperative and OOP background, this book will guide you through the world of functional programming, irrespective of which programming language you use.
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R 611.00
Python Programming and Numerical Methods
Python Programming and Numerical Methods: A Guide for Engineers and Scientists introduces programming tools and numerical methods to engineering and science students, with the goal of helping the students to develop good computational problem-solving techniques through the use of numerical methods and the Python programming language. Part One introduces fundamental programming concepts, using simple examples to put new concepts quickly into practice. Part Two covers the fundamentals of algorithms and numerical analysis at a level that allows students to quickly apply results in practical settings.
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