Search results for "Python in Depth"
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Effective Computation in Physics
More physicists today are taking on the role of software developer as part of their research, but software development isn't always easy or obvious, even for physicists. This practical book teaches essential software development skills to help you automate and accomplish nearly any aspect of research in a physics-based field. Written by two PhDs in nuclear engineering, this book includes practical examples drawn from a working knowledge of physics concepts. You'll learn how to use the Python programming language to perform everything from collecting and analyzing data to building software and publishing your results.In four parts, this book includes: Getting Started: Jump into Python, the command line, data containers, functions, flow control and logic, and classes and objects Getting It Done: Learn about regular expressions, analysis and visualization, NumPy, storing data in files and HDF5, important data structures in physics, computing in parallel, and deploying software Getting It Right: Build pipelines and software, learn to use local and remote version control, and debug and test your code Getting It Out There: Document your code, process and publish your findings, and collaborate efficiently; dive into software licenses, ownership, and copyright procedures
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Python Programming on WIN32
Python is growing in popularity; based on download statistics, there are now over 450,000 people using Python, and more than 150,000 people using Python on Windows. Use of the language has been growing at about 40% per year since 1995, and there is every reason to believe that growth will continue. Despite Python's increasing popularity on Windows, Python Programming on Win32 is the first book to demonstrate how to use it as a serious Windows development and administration tool. Unlike scripting on Unix, Windows scripting involves integrating a number of components, such as COM or the various mail and database APIs, with the Win32 programming interface. While experienced Windows C++ programmers can find their way through the various objects, most people need some guidance, and this book is it. It addresses all the basic technologies for common integration tasks on Windows, explaining both the Windows issues and the Python code you need to glue things together.Topics include: * The Python language and the PythonWin extensions * Building a GUI with COM * Adding a Macro language * Distributing the application * Client-side COM for output and data access * Integration with mail and other internet protocols * Managing users and drives This is a vital and unique book. Python Programming on Win32 is an excellent presentation of Windows application development and a solid illustration of how to use Python in the Windows environment.
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Pragmatic Python Programming
Explore the world of programming languages through Python and learn the building blocks of writing programs. This book covers Python 3.10, explaining it through six key concepts. Each chapter contains a real-world example with practical advice and a section on advanced concepts. You'll start by reviewing the concept of expressions and functions, which are two of the core building blocks of programming languages. You'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs. The book also takes a close look at sequences, explaining constructs and additional types, and wraps up with a chapter on modules, focusing on how to use and create packages. Whether you’re new to programming or already an experienced developer, upon finishing this book, you will have a solid understanding of Python's state-of-the-art development features.What You Will LearnStudy the six main concepts of the programming languagesLearn how to use programming language constructs through examplesReview the core Python language notations and concepts.Start using Python as a working languageWho This Book Is ForSoftware developers wanting to gain professional core Python knowledge quickly, and non-developers wanting to gain an understanding of programming concepts.
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Introduction to Python Programming and Data Structures, Global Edition
For introductory courses in Python Programming and Data Structures. A fundamentals first approach to programming helps students create efficient, elegant code. Introduction to Python Programming and Data Structures introduces students to basic programming concepts using a fundamentals-first approach that prepares students to learn object-oriented programming and advanced Python programming. This approach presents programming concepts and techniques that include control statements, loops, functions, and arrays before designing custom classes. Students learn basic logic and programming concepts prior to moving into object-oriented and GUI programming. The content incorporates a wide variety of problems with various levels of difficulty and covers many application areas to engage and motivate students.
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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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Python for Signal Processing
This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to “experiment and learn” as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remain unchanged into the foreseeable future. For those looking to migrate their signal processing codes to Python, this book illustrates the key signal and plotting modules that can ease this transition. For those already comfortable with the scientific Python toolchain, this book illustrates the fundamental concepts in signal processing and provides a gateway to further signal processing concepts.
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Python
This title is part of UC Press's Voices Revived program, which commemorates University of California Press’s mission to seek out and cultivate the brightest minds and give them voice, reach, and impact. Drawing on a backlist dating to 1893, Voices Revived makes high-quality, peer-reviewed scholarship accessible once again using print-on-demand technology. This title was originally published in 1959.
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Python
This book is an introduction to programming concepts that uses Python 3 as the target language. It follows a practical just in time presentation – material is given to the student when it is needed. Many examples will be based on games because Python has become the language of choice for basic game development. Designed as a year 1 textbook for introduction to programming classes or for the hobbyist who wants to learn the fundamentals of programming, the text assumes no programming experience.FEATURES:Introduces programming concepts using Python 3.Covers basic computer concepts such as loops, strings, functions, files, graphics, multimedia, algorithms, classes, writing code, etc. Develops graphics, exercises, and user interface using Pygame.Includes many examples based on video game development.4 color throughout with game demos on the companion files.New chapters on parsing (14) and graphics (15).Instructor ancillaries for use as a textbook.
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Python Programming in A Day
Python Programming In A Day 2nd Edition: Beginners Power Guide To Learning Python Programming From Scratch What exactly is python programming and is it really that complex? How is Python made so easy so the jargon is gone and you can have success programming within a day? Want to know all about interactive mode with mathematical operations? Variables? Strings? Mr. Key is going above and beyond with data types, programming modes and conditional statements Always wanted a step by step guide to begin a program building from start to finish? Look no further! Its time for you to take advantage of this easy programming guide so you can have immediate success in Python Programming! But Now!
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Artificial Intelligence with Python
Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around youAbout This Book• Step into the amazing world of intelligent apps using this comprehensive guide• Enter the world of Artificial Intelligence, explore it, and create your own applications• Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no timeWho This Book Is ForThis book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks.What You Will Learn• Realize different classification and regression techniques• Understand the concept of clustering and how to use it to automatically segment data• See how to build an intelligent recommender system• Understand logic programming and how to use it• Build automatic speech recognition systems• Understand the basics of heuristic search and genetic programming• Develop games using Artificial Intelligence• Learn how reinforcement learning works• Discover how to build intelligent applications centered on images, text, and time series data• See how to use deep learning algorithms and build applications based on itIn DetailArtificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications.During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide!Style and approachThis highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application.
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Powerful Python
Learn the 5% of Python programming knowledge which exponentially accelerates your learning curve for the remaining 95%.Alleviate the overwhelm of "too much to learn, not enough time". This book cuts through the noise to focus on the "accelerators" that rapidly move the needle.Discover Python's key abstractions which enable and power the most important Python libraries, including Pandas; Django; Flask; SQLAlchemy; Twisted; Pytest; and more.Top Python programming performance is closer than you think. The difference between the best and the rest lies in the distinctions they make, the mental models they leverage, and their ability to perceive what others cannot. Powerful Python cuts through the noise to focus on these performance accelerators which rapidly improve your coding level and yield the most benefit on real-world production engineering and data teams.After a brief tour of the most necessary programming fundamentals; coding techniques and libraries including Pandas, Django, Flask, SQLAlchemy, Twisted, and Pytest are explored to unlock huge capabilities for the reader. Complex patterns are explained with only the minimum detail needed for use, and frequent code examples are used to show all methods in practice. For those ready to move beyond junior programmer stage, this book provides the 5% of knowledge that makes the remaining 95% of the journey a walk in the park.
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Natural Language Understanding with Python
Build advanced Natural Language Understanding Systems by acquiring data and selecting appropriate technology.Key FeaturesMaster NLU concepts from basic text processing to advanced deep learning techniquesExplore practical NLU applications like chatbots, sentiment analysis, and language translationGain a deeper understanding of large language models like ChatGPTBook DescriptionNatural language understanding (NLU) organizes and structures, language allowing computer systems to effectively process textual information for many different practical applications. Natural Language Understanding with Python will help you explore practical techniques that make use of NLU to build a wide variety of creative and useful applications.Complete with step-by-step explanations of essential concepts and practical examples, this book begins by teaching you about NLU and its applications. You’ll then explore a wide range of current NLU techniques and their most appropriate use-case. In the process, you’ll be introduced to the most useful Python NLU libraries. Not only will you learn the basics of NLU, you’ll also be introduced to practical issues such as acquiring data, evaluating systems, and deploying NLU applications, along with their solutions. This book is a comprehensive guide that will help you explore the full spectrum of essential NLU techniques and resources.By the end of this book, you will be familiar with the foundational concepts of NLU, deep learning, and large language models (LLMs). You will be well on your way to having the skills to independently apply NLU technology in your own academic and practical applications.What you will learnThe most important skill that readers will acquire is not just HOW to apply natural language techniques, but WHY to select particular techniques.The book will also cover important practical considerations concerning acquiring real data and evaluating real system performance, not just performing textbook evaluations with pre-existing corpora.After reading this book and studying the code, readers will be equipped to build state of the art as well as practical natural language applications to solve real problems.How to develop and fine-tune an NLP applicationMaintaining NLP applications after deploymentWho this book is forThis book is for python developers, computational linguists, linguists, data scientists, NLP developers, conversational AI developers, and students looking to learn about natural language understanding (NLU) and applying natural language processing (NLP) technology to real problems. Anyone interested in addressing natural language problems will find this book useful. Working knowledge in Python is a must.
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Hands-On Web Scraping with Python
Collect and scrape different complexities of data from the modern Web using the latest tools, best practices, and techniquesKey FeaturesLearn various scraping techniques using a range of Python libraries such as Scrapy and Beautiful SoupBuild scrapers and crawlers to extract relevant information from the webAutomate web scraping operations to bridge the accuracy gap and ease complex business needsBook DescriptionWeb scraping is an essential technique used in many organizations to scrape valuable data from web pages. This book will enable you to delve deeply into web scraping techniques and methodologies. This book will introduce you to the fundamental concepts of web scraping techniques and how they can be applied to multiple sets of web pages. We'll use powerful libraries from the Python ecosystem—such as Scrapy, lxml, pyquery, bs4, and others—to carry out web scraping operations. We will take an in-depth look at essential tasks to carry out simple to intermediate scraping operations such as identifying information from web pages, using patterns or attributes to retrieve information, and others. This book adopts a practical approach to web scraping concepts and tools, guiding you through a series of use cases and showing you how to use the best tools and techniques to efficiently scrape web pages. This book also covers the use of other popular web scraping tools, such as Selenium, Regex, and web-based APIs.By the end of this book, you will have learned how to efficiently scrape the web using different techniques with Python and other popular tools.What you will learnAnalyze data and Information from web pagesLearn how to use browser-based developer tools from the scraping perspectiveUse XPath and CSS selectors to identify and explore markup elementsLearn to handle and manage cookiesExplore advanced concepts in handling HTML forms and processing loginsOptimize web securities, data storage, and API use to scrape dataUse Regex with Python to extract dataDeal with complex web entities by using Selenium to find and extract dataWho this book is forThis book is for Python programmers, data analysts, web scraping newbies, and anyone who wants to learn how to perform web scraping from scratch. If you want to begin your journey in applying web scraping techniques to a range of web pages, then this book is what you need! A working knowledge of the Python programming language is expected.
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Python Scripting for Computational Science
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
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