Search results for "Master Multi-Paradigm Python Programming"
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Essential Programming for the Technical Artist
This book is based on a successful curriculum designed to elevate technical artists with no programming experience up to essential programming competency as quickly as possible. Instead of abstract, theoretical problems, the curriculum employs familiar applications encountered in real production environments to demonstrate each lesson.Written with artists in mind, this book introduces novice programmers to the advantageous world of Python programming with relevant and familiar examples. Any digital artists (not just technical artists) will find this book helpful in assisting with day-to-day production activities.Concentrating upon subjects relevant to the creation of computer graphic assets, this book introduces Python basics, functions, data types, object-oriented programming, exception handling, file processing, graphical user interface creation, PEP 8 standards, and regular expressions. Programming within the SideFX Houdini 3D animation software provides a familiar environment for artists to create and experiment with the covered Python topics.
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Distributed Programming
Distributed Programming: Theory and Practice presents a practical and rigorous method to develop distributed programs that correctly implement their specifications. The method also covers how to write specifications and how to use them. Numerous examples such as bounded buffers, distributed locks, message-passing services, and distributed termination detection illustrate the method. Larger examples include data transfer protocols, distributed shared memory, and TCP network sockets. Distributed Programming: Theory and Practice bridges the gap between books that focus on specific concurrent programming languages and books that focus on distributed algorithms. Programs are written in a "real-life" programming notation, along the lines of Java and Python with explicit instantiation of threads and programs. Students and programmers will see these as programs and not "merely" algorithms in pseudo-code. The programs implement interesting algorithms and solve problems that are large enough to serve as projects in programming classes and software engineering classes. Exercises and examples are included at the end of each chapter with on-line access to the solutions. Distributed Programming: Theory and Practice is designed as an advanced-level text book for students in computer science and electrical engineering. Programmers, software engineers and researchers working in this field will also find this book useful.
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Head First Programming
Looking for a reliable way to learn how to program on your own, without being overwhelmed by confusing concepts? "Head First Programming" introduces the core concepts of writing computer programs - variables, decisions, loops, functions, and objects - which apply regardless of the programming language. This book offers concrete examples and exercises in the dynamic and versatile Python language to demonstrate and reinforce these concepts. You can learn the basic tools to start writing the programs that interest you, and get a better understanding of what software can (and cannot) do. When you're finished, you'll have the necessary foundation to learn any programming language or tackle any software project you choose.With a focus on programming concepts, this book teaches you how to: understand the core features of all programming languages, including variables, statements, decisions, loops, expressions, and operators; reuse code with functions; use library code to save time and effort; select the best data structure to manage complex data; write programs that talk to the Web; share your data with other programs; and, write programs that test themselves and help you avoid embarrassing coding errors. We think your time is too valuable to waste struggling with new concepts. Using the latest research in cognitive science and learning theory to craft a multi-sensory learning experience, "Head First Programming" uses a visually rich format designed for the way your brain works, not a text-heavy approach that puts you to sleep.
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Building Data-Driven Applications with LlamaIndex
Build data-grounded AI applications with LlamaIndex through hands-on examples covering RAG pipelines, agentic workflows, multi-agent systems, prompt engineering, evaluation, and deployment with Python and Streamlit.Free with your book: DRM-free PDF version + access to Packt's next-gen Reader*Key FeaturesBuild complete RAG pipelines from ingestion to deployment with practical working examplesDesign agentic workflows and multi-agent architectures for production-ready AI systemsDevelop a hands-on project from a simple LLM app to a deployed AI-powered web applicationRun everything locally with Ollama - no API keys or costs requiredBook DescriptionLarge language models can generate impressive responses, but they often struggle with outdated knowledge, limited access to proprietary data, hallucinations, and inconsistent reasoning in real-world applications. LlamaIndex addresses these challenges through RAG, enabling developers to connect LLMs with external data sources and build more reliable AI applications.This fully updated second edition reflects the latest evolution of the LlamaIndex ecosystem. You will learn how to ingest and parse data from multiple sources, build optimized indexes, and implement advanced retrieval strategies for high-quality RAG applications.The book introduces modern agentic AI patterns using LlamaIndex Workflows, chat engines, agents, and multi-agent orchestration. You will also explore observability and RAG evaluation, prompt engineering best practices, and deployment strategies using Streamlit.Throughout the book, you will build a practical Contract Review Expert application that evolves chapter by chapter from a simple query engine into a fully deployed AI-powered web application. You will also learn how to use enterprise tooling such as LlamaParse alongside open source alternatives such as LiteParse.By the end of this book, you will be able to design, build, evaluate, and deploy scalable LlamaIndex applications grounded in your own data.*Email sign-up and proof of purchase requiredWhat you will learnUnderstand the LlamaIndex ecosystem and core use casesMaster techniques to ingest and parse data from diverse sourcesBuild optimized indexes for RAG applicationsQuery data using retrievers, postprocessors, and response synthesizersDesign agentic workflows and multi-agent systemsDeploy AI applications with Python and StreamlitEvaluate and tune your RAG implementation using observability tools and key metricsApply prompt engineering best practices to improve AI responsesWho this book is forThis book is for Python developers with a basic knowledge of LLMs who want to build interactive, generative, and agentic AI applications grounded in proprietary data. Experienced developers and AI practitioners will also benefit from the advanced techniques covered like agentic workflows, multi-agent orchestration, RAG evaluation, and enterprise tooling. A working knowledge of Python and familiarity with generative AI concepts is assumed.The b
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Web Development with Django 6
Create modern, secure websites easily and quickly with Django 6 through realistic case studies updated for the latest async features and modern Python supportKey FeaturesGet to grips with Django 6 functionality, the MVT paradigm, and its new async-powered featuresBuild and extend a book-review site using updated templates, forms, async features, and ORM toolsExplore REST APIs, async views, third-party integrations, testing, and modern deployment optionsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionTired of spending hours on boilerplate code when you should be building features? Django 6 transforms your workflow with major improvements to the Python web ecosystem—from expanded async support to improved form rendering, stronger security, and modern template and ORM capabilities. This book shows you how to take full advantage of these upgrades to build reliable, secure, and high-performance web applications in a structured, hands-on way.You’ll discover Django 6’s power by building an end-to-end case study of developing a website called Bookr, a repository for book reviews that mirrors real development workflows. Through guided practical exercises, you'll learn how to serve static files, implement forms using Django 6’s improved rendering system, handle async views and ORM operations, and manage sessions to create a seamless user experience. You’ll also tackle essential tasks such as authentication, security best practices, and integrating modern front-end tools.By the end of this Django book, you’ll be ready to build and deploy your own scalable, modern Python web applications using Django 6.What you will learnStart a new Django 6 project and define models using the improved ORMWork with function and class-based views using templates to control application behaviorImplement authentication, permissions, and modern session handling techniquesCreate practical forms using Django 6's updated rendering APIBuild RESTful APIs and the JavaScript features that integrate with themConnect to PostgreSQL and run async-ready queries where supportedWho this book is forThis book is for programmers who want to enhance their web development skills with Django 6. You’ll get the most out of it if you already know Python programming and are familiar with JavaScript, HTML, and CSS. This book is especially useful for anyone looking to understand Django’s new async capabilities, modern security features, and production-ready web development patterns.
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Machine Learning with LightGBM and Python
Take your software to the next level and solve real-world data science problems by building production-ready machine learning solutions using LightGBM and PythonKey FeaturesGet started with LightGBM, a powerful gradient-boosting library for building ML solutionsApply data science processes to real-world problems through case studiesElevate your software by building machine learning solutions on scalable platformsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionMachine Learning with LightGBM and Python is a comprehensive guide to learning the basics of machine learning and progressing to building scalable machine learning systems that are ready for release.This book will get you acquainted with the high-performance gradient-boosting LightGBM framework and show you how it can be used to solve various machine-learning problems to produce highly accurate, robust, and predictive solutions. Starting with simple machine learning models in scikit-learn, you’ll explore the intricacies of gradient boosting machines and LightGBM. You’ll be guided through various case studies to better understand the data science processes and learn how to practically apply your skills to real-world problems. As you progress, you’ll elevate your software engineering skills by learning how to build and integrate scalable machine-learning pipelines to process data, train models, and deploy them to serve secure APIs using Python tools such as FastAPI.By the end of this book, you’ll be well equipped to use various -of-the-art tools that will help you build production-ready systems, including FLAML for AutoML, PostgresML for operating ML pipelines using Postgres, high-performance distributed training and serving via Dask, and creating and running models in the Cloud with AWS Sagemaker.What you will learnGet an overview of ML and working with data and models in Python using scikit-learnExplore decision trees, ensemble learning, gradient boosting, DART, and GOSSMaster LightGBM and apply it to classification and regression problemsTune and train your models using AutoML with FLAML and OptunaBuild ML pipelines in Python to train and deploy models with secure and performant APIsScale your solutions to production readiness with AWS Sagemaker, PostgresML, and DaskWho this book is forThis book is for software engineers aspiring to be better machine learning engineers and data scientists unfamiliar with LightGBM, looking to gain in-depth knowledge of its libraries. Basic to intermediate Python programming knowledge is required to get started with the book.The book is also an excellent source for ML veterans, with a strong focus on ML engineering with up-to-date and thorough coverage of platforms such as AWS Sagemaker, PostgresML, and Dask.
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Programming the Intel Edison: Getting Started with Processing and Python
Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product.Learn To Easily Create Robotic, IoT, and Wearable Electronic Gadgets!Get up-and-running building cutting-edge Edison devices with help from this DIY guide. Programming the Intel Edison: Getting Started with Processing and Python lays out the Edison’s powerful features and teaches the basics of Internet-enabled embedded programming. Discover how to set up components, connect your PC or Mac, build Python applications, and use USB, WiFi, and Bluetooth connections. Start-to-finish example projects include a motor controller, home temperature system, robotic car, and wearable hospital alert sensor.Explore the capabilities and features of the EdisonConnect Sparkfun, Break-out, and Arduino boardsProgram your Edison through the Arduino IDESet up USB, GPIO, WiFi, and Bluetooth connections
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Mathematical Programming for Power Systems Operation
Explore the theoretical foundations and real-world power system applications of convex programming In Mathematical Programming for Power System Operation with Applications in Python, Professor Alejandro Garces delivers a comprehensive overview of power system operations models with a focus on convex optimization models and their implementation in Python. Divided into two parts, the book begins with a theoretical analysis of convex optimization models before moving on to related applications in power systems operations. The author eschews concepts of topology and functional analysis found in more mathematically oriented books in favor of a more natural approach. Using this perspective, he presents recent applications of convex optimization in power system operations problems. Mathematical Programming for Power System Operation with Applications in Python uses Python and CVXPY as tools to solve power system optimization problems and includes models that can be solved with the presented framework. The book also includes: A thorough introduction to power system operation, including economic and environmental dispatch, optimal power flow, and hosting capacityComprehensive explorations of the mathematical background of power system operation, including quadratic forms and norms and the basic theory of optimizationPractical discussions of convex functions and convex sets, including affine and linear spaces, politopes, balls, and ellipsoidsIn-depth examinations of convex optimization, including global optimums, and first and second order conditions Perfect for undergraduate students with some knowledge in power systems analysis, generation, or distribution, Mathematical Programming for Power System Operation with Applications in Python is also an ideal resource for graduate students and engineers practicing in the area of power system optimization.
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Mastering Parallel Programming with R
Master the robust features of R parallel programming to accelerate your data science computationsAbout This Book• Create R programs that exploit the computational capability of your cloud platforms and computers to the fullest• Become an expert in writing the most efficient and highest performance parallel algorithms in R• Get to grips with the concept of parallelism to accelerate your existing R programsWho This Book Is ForThis book is for R programmers who want to step beyond its inherent single-threaded and restricted memory limitations and learn how to implement highly accelerated and scalable algorithms that are a necessity for the performant processing of Big Data. No previous knowledge of parallelism is required. This book also provides for the more advanced technical programmer seeking to go beyond high level parallel frameworks.What You Will Learn• Create and structure efficient load-balanced parallel computation in R, using R's built-in parallel package• Deploy and utilize cloud-based parallel infrastructure from R, including launching a distributed computation on Hadoop running on Amazon Web Services (AWS)• Get accustomed to parallel efficiency, and apply simple techniques to benchmark, measure speed and target improvement in your own code• Develop complex parallel processing algorithms with the standard Message Passing Interface (MPI) using RMPI, pbdMPI, and SPRINT packages• Build and extend a parallel R package (SPRINT) with your own MPI-based routines• Implement accelerated numerical functions in R utilizing the vector processing capability of your Graphics Processing Unit (GPU) with OpenCL• Understand parallel programming pitfalls, such as deadlock and numerical instability, and the approaches to handle and avoid them• Build a task farm master-worker, spatial grid, and hybrid parallel R programsIn DetailR is one of the most popular programming languages used in data science. Applying R to big data and complex analytic tasks requires the harnessing of scalable compute resources.Mastering Parallel Programming with R presents a comprehensive and practical treatise on how to build highly scalable and efficient algorithms in R. It will teach you a variety of parallelization techniques, from simple use of R's built-in parallel package versions of lapply(), to high-level AWS cloud-based Hadoop and Apache Spark frameworks. It will also teach you low level scalable parallel programming using RMPI and pbdMPI for message passing, applicable to clusters and supercomputers, and how to exploit thousand-fold simple processor GPUs through ROpenCL. By the end of the book, you will understand the factors that influence parallel efficiency, including assessing code performance and implementing load balancing; pitfalls to avoid, including deadlock and numerical instability issues; how to structure your code and data for the most appropriate type of parallelism for your problem domain; and how to extract the maximum performance from your R code running
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