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Supercharged Coding with GenAI
Unlock the power of generative AI in Python development and learn how you can enhance your coding speed, quality, and efficiency with real-world examples and hands-on strategiesKey FeaturesDiscover how GitHub Copilot, ChatGPT, and the OpenAI API can boost your coding productivityPush beyond the basics to apply advanced techniques across the software development lifecycleMaster best practices and advanced techniques to achieve quality code for even complex tasksPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionSoftware development is being transformed by GenAI tools, such as ChatGPT, OpenAI API, and GitHub Copilot, redefining how developers work. This book will help you become a power user of GenAI for Python code generation, enabling you to write better software faster. Written by an ML advisor with a thriving tech social media presence and a top AI leader who brings Harvard-level instruction to the table, this book combines practical industry insights with academic expertise.With this book, you'll gain a deep understanding of large language models (LLMs) and develop a systematic approach to solving complex tasks with AI. Through real-world examples and practical exercises, you’ll master best practices for leveraging GenAI, including prompt engineering techniques like few-shot learning and Chain-of-Thought (CoT).Going beyond simple code generation, this book teaches you how to automate debugging, refactoring, performance optimization, testing, and monitoring. By applying reusable prompt frameworks and AI-driven workflows, you’ll streamline your software development lifecycle (SDLC) and produce high-quality, well-structured code.By the end of this book, you'll know how to select the right AI tool for each task, boost efficiency, and anticipate your next coding moves—helping you stay ahead in the AI-powered development era.What you will learnWork with GitHub Copilot in PyCharm, VS Code, and Jupyter NotebookApply advanced prompting methods with ChatGPT and OpenAI APIGain insight into GenAI fundamentals to achieve better outcomesAdopt our structured framework to produce high-quality codeFind out how to select the optimal GenAI tool for solving your specific tasksElevate your use of GenAI tools from debugging to deliveryJoin the next generation of supercharged software engineersWho this book is forIf you are a Python developer curious about GenAI and are looking to elevate your software engineering productivity, Supercharged Coding with GenAI will transform your approach to software. Covering various structured examples of varying problem complexities that showcase the use of advanced prompting techniques, this book is suitable for early intermediate through advanced developers. To get the most out of this book, you should have at least one year of hands-on Python development experience and be somewhat familiar with the SDLC.
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Modern Django Web Development
Django has evolved into a powerful full-stack framework ideal for developing data-driven web applications, continuously expanding with new tools for asynchronous solutions, APIs, and real-time applications. This book explores modern Django development best practices, including Django Channels for WebSockets, Django REST Framework (DRF) for REST APIs, Graphene and Strawberry for GraphQL APIs, and integrating a front-end built with React The content is structured into two main parts, covering both fundamental and advanced concepts in a practical and digestible manner. The first part introduces Django's core concepts, starting with an overview of web development and Python's asyncio module for asynchronous processing. It then walks you through Django installation, project setup, and the admin interface. The Model-View-Template (MVT) architecture is explained in depth, with chapters on models, views, and templates, illustrating real-world examples. Additionally, it covers database interactions, introducing SQLAlchemy ORM and MongoDB integration to extend Django's capabilities beyond its default ORM. The second part delves into advanced Django features and the broader ecosystem. Topics include authentication, security, messaging, and reusable apps such as the Django toolbar. REST API development with Django REST Framework is explored, followed by an introduction to building GraphQL APIs using Graphene and Strawberry. A dedicated chapter covers Django Channels and the WebSocket protocol for real-time applications. Modern Django Web Development concludes with integrating React to develop front-end clients for Django-based REST, GraphQL, and WebSocket APIs, enabling a full-stack development experience. You Will: Explore the full spectrum of modern Django developmentLearn how to use SQLAlchemy MongoDB with DjangoUnderstand Django Channels for asynchronous web appsExplore DRF for building REST API in DjangoLearn how to build GraphQL API with Graphene and StrawberryUnderstand how to develop a Django-React app Who is it for: Software developers, web developers and engineers who are interested in adding Django to their development skillset. Python Developers can also leverage the power of modern Django with the help of this practical guide.
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Python Machine Learning
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning.Purchase of the print or Kindle book includes a free eBook in the PDF format.Key FeaturesThird edition of the bestselling, widely acclaimed Python machine learning bookClear and intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practicesBook DescriptionPython Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself.Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents.This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.What you will learnMaster the frameworks, models, and techniques that enable machines to 'learn' from dataUse scikit-learn for machine learning and TensorFlow for deep learningApply machine learning to image classification, sentiment analysis, intelligent web applications, and moreBuild and train neural networks, GANs, and other modelsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.
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Python Experiments in Physics and Astronomy
Python Experiments in Physics and Astronomy acts as a resource for science and engineering students or faculty who would like to see how a diverse selection of topics can be analyzed and simulated using Python programs. The book also provides Python solutions that can be learned from and modified as needed. The book is mainly aimed at undergraduates, but since many science students and faculty have limited exposure to scientific programming, having a collection of examples that address curve-fitting, Fast Fourier Transforms, image photometry and image alignment, and many others could be very helpful not just for learning from, but also to support classroom projects and demonstrations.Key Features:Features tutorials using Python for non-computer science students and faculty involved with scientific programmingContains complete scientific programming examples for teaching and academic projectsPresents detailed Python solutions for Physics and Astronomy topics, not normally covered in depth, because they would be too time-consumingPurchasers of the book can access the accompanying computer code via the Instructor Resources Download Hub.
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Clean Code in Python
Getting the most out of Python to improve your codebaseKey FeaturesSave maintenance costs by learning to fix your legacy codebaseLearn the principles and techniques of refactoringApply microservices to your legacy systems by implementing practical techniquesBook DescriptionPython is currently used in many different areas such as software construction, systems administration, and data processing. In all of these areas, experienced professionals can find examples of inefficiency, problems, and other perils, as a result of bad code. After reading this book, readers will understand these problems, and more importantly, how to correct them. The book begins by describing the basic elements of writing clean code and how it plays an important role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. You will learn to implement the SOLID principles in Python and use decorators to improve your code. The book delves more deeply into object oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve software problems by implementing design patterns in your code. In the final chapter we break down a monolithic application to a microservice one, starting from the code as the basis for a solid platform. By the end of the book, you will be proficient in applying industry approved coding practices to design clean, sustainable and readable Python code. What you will learnSet up tools to effectively work in a development environmentExplore how the magic methods of Python can help us write better codeExamine the traits of Python to create advanced object-oriented designUnderstand removal of duplicated code using decorators and descriptorsEffectively refactor code with the help of unit testsLearn to implement the SOLID principles in PythonWho this book is forThis book will appeal to team leads, software architects and senior software engineers who would like to work on their legacy systems to save cost and improve efficiency. A strong understanding of Programming is assumed.
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Intermediate Python and Large Language Models
Harness the power of Large Language Models (LLMs) to build cutting-edge AI applications with Python and LangChain. This book provides a hands-on approach to understanding, implementing, and deploying LLM-powered solutions, equipping developers, data scientists, and AI enthusiasts with the tools to create real-world AI applications. The journey begins with an introduction to LangChain, covering its core concepts, integration with Python, and essential components such as prompt engineering, memory management, and retrieval-augmented generation (RAG). As you progress, you'll explore advanced AI workflows, including multi-agent architectures, fine-tuning strategies, and optimization techniques to maximize LLM efficiency. The book also takes a deep dive into practical applications of LLMs, guiding you through the development of intelligent chatbots, document retrieval systems, content generation pipelines, and AI-driven automation tools. You'll learn how to leverage APIs, integrate LLMs into web and mobile platforms, and optimize large-scale deployments while addressing key challenges such as inference latency, cost efficiency, and ethical considerations. By the end of the book, you'll have gained a solid understanding of LLM architectures, hands-on experience with LangChain, and the expertise to build scalable AI applications that redefine human-computer interaction. What You Will Learn Understand the fundamentals of LangChain and Python for LLM development Know advanced AI workflows, including fine-tuning and memory management Build AI-powered applications such as chatbots, retrieval systems, and automation tools Know deployment strategies and performance optimization for real-world use Use best practices for scalability, security, and responsible AI implementation Unlock the full potential of LLMs and take your AI development skills to the next level Who This Book Is For Software engineers and Python developers interested in learning the foundations of LLMs and building advanced modern LLM applications for various tasks
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Introducing Python
Stuck in a coding conundrum? Whether you're an advanced beginner, an intermediate developer, or a curious newcomer, the complexities of coding can often feel like a labyrinth with no exit. With Python, however, you can start writing real code quickly-but where should you start?In this updated third edition, Bill Lubanovic acts as your personal guide to Python, offering a clear path through the intricacies and capabilities of this much-beloved coding language, including new chapters on AI models and performance enhancements. Easy to understand and enjoyable to read, this book not only teaches you the core concepts but also dives into practical applications that bridge the gap between learning and doing. By reading it, you will:Understand everything from basic data structures to advanced featuresGain insights into using Python for files, networking, databases, and data scienceLearn testing, debugging, code reuse, and other essential development tipsExplore how Python can be utilized in business, science, and the arts
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Clean Code in Python
Tackle inefficiencies and errors the Pythonic wayKey FeaturesEnhance your coding skills using the new features introduced in Python 3.9Implement the refactoring techniques and SOLID principles in PythonApply microservices to your legacy systems by implementing practical techniquesBook DescriptionExperienced professionals in every field face several instances of disorganization, poor readability, and testability due to unstructured code. With updated code and revised content aligned to the new features of Python 3.9, this second edition of Clean Code in Python will provide you with all the tools you need to overcome these obstacles and manage your projects successfully. The book begins by describing the basic elements of writing clean code and how it plays a key role in Python programming. You will learn about writing efficient and readable code using the Python standard library and best practices for software design. The book discusses object-oriented programming in Python and shows you how to use objects with descriptors and generators. It will also show you the design principles of software testing and how to resolve problems by implementing software design patterns in your code. In the concluding chapter, we break down a monolithic application into a microservices-based one starting from the code as the basis for a solid platform. By the end of this clean code book, you will be proficient in applying industry-approved coding practices to design clean, sustainable, and readable real-world Python code.What you will learnSet up a productive development environment by leveraging automatic toolsLeverage the magic methods in Python to write better code, abstracting complexity away and encapsulating detailsCreate advanced object-oriented designs using unique features of Python, such as descriptorsEliminate duplicated code by creating powerful abstractions using software engineering principles of object-oriented designCreate Python-specific solutions using decorators and descriptorsRefactor code effectively with the help of unit testsBuild the foundations for solid architecture with a clean code base as its cornerstoneWho this book is forThis book is designed to benefit new as well as experienced programmers. It will appeal to team leads, software architects and senior software engineers who would like to write Pythonic code to save on costs and improve efficiency. The book assumes that you have a strong understanding of programming
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Python Natural Language Processing Cookbook
Updated to include three new chapters on transformers, natural language understanding (NLU) with explainable AI, and dabbling with popular LLMs from Hugging Face and OpenAIKey FeaturesLeverage ready-to-use recipes with the latest LLMs, including Mistral, Llama, and OpenAI modelsUse LLM-powered agents for custom tasks and real-world interactionsGain practical, in-depth knowledge of transformers and their role in implementing various NLP tasks with open-source and advanced LLMsPurchase of the print or Kindle book includes a free PDF eBookBook DescriptionHarness the power of Natural Language Processing to overcome real-world text analysis challenges with this recipe-based roadmap written by two seasoned NLP experts with vast experience transforming various industries with their NLP prowess.You’ll be able to make the most of the latest NLP advancements, including large language models (LLMs), and leverage their capabilities through Hugging Face transformers. Through a series of hands-on recipes, you’ll master essential techniques such as extracting entities and visualizing text data. The authors will expertly guide you through building pipelines for sentiment analysis, topic modeling, and question-answering using popular libraries like spaCy, Gensim, and NLTK. You’ll also learn to implement RAG pipelines to draw out precise answers from a text corpus using LLMs.This second edition expands your skillset with new chapters on cutting-edge LLMs like GPT-4, Natural Language Understanding (NLU), and Explainable AI (XAI)—fostering trust and transparency in your NLP models.By the end of this book, you'll be equipped with the skills to apply advanced text processing techniques, use pre-trained transformer models, build custom NLP pipelines to extract valuable insights from text data to drive informed decision-making.What you will learnUnderstand fundamental NLP concepts along with their applications using examples in PythonClassify text quickly and accurately with rule-based and supervised methodsTrain NER models and perform sentiment analysis to identify entities and emotions in textExplore topic modeling and text visualization to reveal themes and relationships within textLeverage Hugging Face and OpenAI LLMs to perform advanced NLP tasksUse question-answering techniques to handle both open and closed domainsApply XAI techniques to better understand your model predictionsWho this book is forThis updated edition of the Python Natural Language Processing Cookbook is for data scientists, machine learning engineers, and developers with a background in Python. Whether you’re looking to learn NLP techniques, extract valuable insights from textual data, or create foundational applications, this book will equip you with basic to intermediate skills. No prior NLP knowledge is necessary to get started. All you need is familiarity with basic programming principles. For seasoned developers, the updated sections offer the latest on transformers, explainable AI, and Gene
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Modern Python Cookbook
Enhance your Python skills with the third edition of Modern Python Cookbook with 130+ new and updated recipes covering Python 3.12, including new coverage on graphics, visualizations, dependencies, virtual environments, and more.Purchase of the print or Kindle book includes a free eBook in PDF formatKey FeaturesNew chapters on type matching, data visualization, dependency management, and moreComprehensive coverage of Python 3.12 with updated recipes and techniquesProvides practical examples and detailed explanations to solve real-world problems efficientlyBook DescriptionPython is the go-to language for developers, engineers, data scientists, and hobbyists worldwide. Known for its versatility, Python can efficiently power applications, offering remarkable speed, safety, and scalability. This book distills Python into a collection of straightforward recipes, providing insights into specific language features within various contexts, making it an indispensable resource for mastering Python and using it to handle real-world use cases.The third edition of Modern Python Cookbook provides an in-depth look into Python 3.12, offering more than 140 new and updated recipes that cater to both beginners and experienced developers. This edition introduces new chapters on documentation and style, data visualization with Matplotlib and Pyplot, and advanced dependency management techniques using tools like Poetry and Anaconda. With practical examples and detailed explanations, this cookbook helps developers solve real-world problems, optimize their code, and get up to date with the latest Python features.What you will learnMaster core Python data structures, algorithms, and design patternsImplement object-oriented designs and functional programming featuresUse type matching and annotations to make more expressive programsCreate useful data visualizations with Matplotlib and PyplotManage project dependencies and virtual environments effectivelyFollow best practices for code style and testingCreate clear and trustworthy documentation for your projectsWho this book is forThis Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book offers helpful details and design patterns for learning Python. If you are experienced, it will expand your knowledge base. Fundamental knowledge of Python programming and basic programming principles will be helpful
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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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Learn Python 3 the Hard Way
You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environmentOrganize and write codeFix and break codeBasic mathematicsVariablesStrings and textInteract with usersWork with filesLooping and logicData structures using lists and dictionariesProgram designObject-oriented programmingInheritance and compositionModules, classes, and objectsPython packagingAutomated testingBasic game developmentBasic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experienceJunior developers who know one or two languagesReturning professionals who haven’t written code in yearsSeasoned professionals looking for a fast, simple, crash course in Python 3
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Mastering Algorithms with Python
Gain a solid understanding of algorithms and improve your problem-solving abilities using Python code. With practical examples and clear explanations, this book bridges the gap between dense academic texts and overly simple industry guides. Focusing on the logic behind essential algorithms such as Breadth First Search (BFS), Depth First Search (DFS), Divide-and-Conquer, Greedy Methods, and Dynamic Programming, the book provides ample examples, from easy to more advanced. By connecting these concepts to real-world examples, such as chess strategies and the Seam Carving, the book helps readers better grasp and apply algorithms. Each chapter also includes fully implemented Python code, making it a practical reference. Mastering Algorithms with Python is ideal for IT professionals looking to enhance their skills and approach algorithms with clarity and confidence. What You Will Learn - - - - Who This Book Is For Software developers, data scientists, machine learning professionals and any curious learners about computer algorithms.
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Python 3 - Intensivkurs
Python ist eine vollwertige Programmiersprache, mit der sich auch größere Anwendungen entwickeln lassen. In den letzten Jahren hat sie an Beliebtheit gewonnen, und mit Python 3 steht eine stark erweiterte Version zur Verfügung. In dem Band werden die Werkzeuge und Programmiermöglichkeiten praxisorientiert vorgestellt. Jedes Kapitel beginnt mit einem vollwertigen, lauffähigen Codebeispiel, das jeweils ausführlich analysiert wird. Im Vordergrund stehen die unmittelbare praktische Anwendung und die Realisierung von Projekten mit Python 3.
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