Scipy Recipes
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Scipy Recipes
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Author : V Kishore Ayyadevara
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-12-20
Scipy Recipes written by V Kishore Ayyadevara and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-20 with Computers categories.
Tackle the most sophisticated problems associated with scientific computing and data manipulation using SciPy Key Features Covers a wide range of data science tasks using SciPy, NumPy, pandas, and matplotlib Effective recipes on advanced scientific computations, statistics, data wrangling, data visualization, and more A must-have book if you're looking to solve your data-related problems using SciPy, on-the-go Book Description With the SciPy Stack, you get the power to effectively process, manipulate, and visualize your data using the popular Python language. Utilizing SciPy correctly can sometimes be a very tricky proposition. This book provides the right techniques so you can use SciPy to perform different data science tasks with ease. This book includes hands-on recipes for using the different components of the SciPy Stack such as NumPy, SciPy, matplotlib, and pandas, among others. You will use these libraries to solve real-world problems in linear algebra, numerical analysis, data visualization, and much more. The recipes included in the book will ensure you get a practical understanding not only of how a particular feature in SciPy Stack works, but also of its application to real-world problems. The independent nature of the recipes also ensure that you can pick up any one and learn about a particular feature of SciPy without reading through the other recipes, thus making the book a very handy and useful guide. What you will learn Get a solid foundation in scientific computing using Python Master common tasks related to SciPy and associated libraries such as NumPy, pandas, and matplotlib Perform mathematical operations such as linear algebra and work with the statistical and probability functions in SciPy Master advanced computing such as Discrete Fourier Transform and K-means with the SciPy Stack Implement data wrangling tasks efficiently using pandas Visualize your data through various graphs and charts using matplotlib Who this book is for Python developers, aspiring data scientists, and analysts who want to get started with scientific computing using Python will find this book an indispensable resource. If you want to learn how to manipulate and visualize your data using the SciPy Stack, this book will also help you. A basic understanding of Python programming is all you need to get started.
Python Cookbook
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Author : Alex Martelli
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2002
Python Cookbook written by Alex Martelli and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002 with Computers categories.
ThePython Cookbookis a collection of problems, solutions, and practical examples for Python programmers, written by Python programmers. Over the past year, members of the Python community have contributed material to an online repository of Python recipes hosted by ActiveState. This book contains the best of those recipes, accompanied by overviews and background material by key Python figures. The recipes in thePython Cookbookrange from simple tasks, such as working with dictionaries and list comprehensions, to entire modules that demonstrate templating systems and network monitoring. This book contains over 200 recipes on the following topics: Searching and sorting Manipulating text Working with files and the filesystem Object-oriented programming Dealing with threads and processes System administration Interacting with databases Creating user interfaces Network and web programming Processing XML Distributed programming Debugging and testing Extending Python This book is a treasure trove of useful code for all Python programmers, from novices to advanced practitioners, with contributions from such Python luminaries as Guido Van Rossum, David Ascher, Tim Peters, Paul Prescod, Mark Hammond, and Alex Martelli, as well as over 100 other Python programmers. The recipes highlight Python best practices and can be used directly in day-to-day programming tasks, as a source of ideas, or as a way to learn more about Python. The recipes in thePython Cookbookwere edited by David Ascher, who is on the board of the Python Software Foundation and is the co-author ofLearning Python,and Alex Martelli, who is known for his numerous and exhaustive postings on the Python mailing list. The book contains a foreword by Guido van Rossum, the creator of Python.
Python Knowledge Building Step By Step From The Basics To The First Desktop Application
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Author : Dr. Csaba Dobreff
language : en
Publisher: Deuteron Kft.
Release Date : 2025-02-08
Python Knowledge Building Step By Step From The Basics To The First Desktop Application written by Dr. Csaba Dobreff and has been published by Deuteron Kft. this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-08 with Computers categories.
The aim of this book is to take the reader from the basic knowledge of computing essentials for programming in Python to a level of proficiency that will enable you to write a full-fledged desktop application with a graphical user interface. In a single book, the reader will get essentially the material of three books in a consistent structure: an introduction to the basic concepts and language building blocks, the application of the commonly used standard library modules, and the development of graphical user interfaces. The book starts from scratch, and the subsequent chapters build on each other. Therefore, it can be used as a textbook for beginners who want to learn computer programming and Python. Hence, it can be useful for high school, university, and course students or hobby programmers. This book is particularly recommended for those who wish to attend a Python course but for some reason (caring for a small child, limited mobility, distance, time constraints, etc.) cannot. The book can help in this situation because its content covers the knowledge that is provided in courses from beginner to advanced level, but it can be studied at the reader's own pace. As the presented body of knowledge is gradually deepening and leads to more and more subtle details of the language, this book is also recommended for teachers, engineers, software developers, data analysts, and data scientists. The book can also be used as a handbook. This means that if you have a task to solve or get stuck on a particular feature or detail of the language, and you remember that there was a section, diagram, table, or example in the book about it, you can go back and read it again. However, it is not a reference book in the sense that it is not a concise summary of the language. It is not intended to be a repetition or substitute for the official Python documentation; instead, it supplements it by providing more detailed descriptions of language features and showing the usage through examples or by giving explanations about the background of a particular language element. The primary goal of the book is to help you understand the principles and concepts, to gradually acquire knowledge of the language, and to develop the practical skills needed to create Python programs. In order to facilitate learning and retention of knowledge, along with numerous figures, diagrams, and tables, simple real-life analogies and metaphors are presented in several places in the text. These analogies mainly appear in passages that contain crucial principles or fundamental concepts that are particularly important for progression. As far as the content is concerned, in addition to some of the core principles of programming and software development, the reader is gradually introduced to important terms and language concepts such as object, container, iterator and generator, function and coroutine, function and class decorator, closure, class, abstract class, mixin class, data class, protocol, data and method attribute, method resolution order, property, attribute descriptor, single and multiple inheritance, module, package, polymorphism, static and dynamic typing, strong and weak typing, type hints, and static type checking. In addition to the basic language building blocks and structures, a number of frequently used modules of the standard library are presented in relation to a specific problem. Such sections are particularly useful for modules that may not be easily understood by everyone from the official documentation, such as the decimal module, which supports high precision mathematical calculations, and the tkinter module, which allows making a graphical user interface. This ebook covers the language features up to Python 3.13.
Fluent Python
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Author : Luciano Ramalho
language : en
Publisher: O'Reilly Media
Release Date : 2015
Fluent Python written by Luciano Ramalho and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Computers categories.
Explains how to write idiomatic, effective Python code by leveraging its best features. Python's simplicity quickly lets you become productive with it, but this often means you aren't using everything the language has to offer. By taking you through Python's key language features and libraries, this practical book shows you how to make your code shorter, faster, and more readable all at the same time. --From publisher description.
Python Cookbook
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Author : David Beazley
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2013-05-10
Python Cookbook written by David Beazley and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-05-10 with Computers categories.
If you need help writing programs in Python 3, or want to update older Python 2 code, this book is just the ticket. Packed with practical recipes written and tested with Python 3.3, this unique cookbook is for experienced Python programmers who want to focus on modern tools and idioms. Inside, youâ??ll find complete recipes for more than a dozen topics, covering the core Python language as well as tasks common to a wide variety of application domains. Each recipe contains code samples you can use in your projects right away, along with a discussion about how and why the solution works. Topics include: Data Structures and Algorithms Strings and Text Numbers, Dates, and Times Iterators and Generators Files and I/O Data Encoding and Processing Functions Classes and Objects Metaprogramming Modules and Packages Network and Web Programming Concurrency Utility Scripting and System Administration Testing, Debugging, and Exceptions C Extensions
Scikit Learn Cookbook
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Author : Julian Avila
language : en
Publisher: Packt Publishing Ltd
Release Date : 2017-11-16
Scikit Learn Cookbook written by Julian Avila and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-11-16 with Computers categories.
Learn to use scikit-learn operations and functions for Machine Learning and deep learning applications. About This Book Handle a variety of machine learning tasks effortlessly by leveraging the power of scikit-learn Perform supervised and unsupervised learning with ease, and evaluate the performance of your model Practical, easy to understand recipes aimed at helping you choose the right machine learning algorithm Who This Book Is For Data Analysts already familiar with Python but not so much with scikit-learn, who want quick solutions to the common machine learning problems will find this book to be very useful. If you are a Python programmer who wants to take a dive into the world of machine learning in a practical manner, this book will help you too. What You Will Learn Build predictive models in minutes by using scikit-learn Understand the differences and relationships between Classification and Regression, two types of Supervised Learning. Use distance metrics to predict in Clustering, a type of Unsupervised Learning Find points with similar characteristics with Nearest Neighbors. Use automation and cross-validation to find a best model and focus on it for a data product Choose among the best algorithm of many or use them together in an ensemble. Create your own estimator with the simple syntax of sklearn Explore the feed-forward neural networks available in scikit-learn In Detail Python is quickly becoming the go-to language for analysts and data scientists due to its simplicity and flexibility, and within the Python data space, scikit-learn is the unequivocal choice for machine learning. This book includes walk throughs and solutions to the common as well as the not-so-common problems in machine learning, and how scikit-learn can be leveraged to perform various machine learning tasks effectively. The second edition begins with taking you through recipes on evaluating the statistical properties of data and generates synthetic data for machine learning modelling. As you progress through the chapters, you will comes across recipes that will teach you to implement techniques like data pre-processing, linear regression, logistic regression, K-NN, Naive Bayes, classification, decision trees, Ensembles and much more. Furthermore, you'll learn to optimize your models with multi-class classification, cross validation, model evaluation and dive deeper in to implementing deep learning with scikit-learn. Along with covering the enhanced features on model section, API and new features like classifiers, regressors and estimators the book also contains recipes on evaluating and fine-tuning the performance of your model. By the end of this book, you will have explored plethora of features offered by scikit-learn for Python to solve any machine learning problem you come across. Style and Approach This book consists of practical recipes on scikit-learn that target novices as well as intermediate users. It goes deep into the technical issues, covers additional protocols, and many more real-live examples so that you are able to implement it in your daily life scenarios.
Python Image Processing Cookbook
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Author : Sandipan Dey
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-04-17
Python Image Processing Cookbook written by Sandipan Dey and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-17 with Computers categories.
Explore Keras, scikit-image, open source computer vision (OpenCV), Matplotlib, and a wide range of other Python tools and frameworks to solve real-world image processing problems Key FeaturesDiscover solutions to complex image processing tasks using Python tools such as scikit-image and KerasLearn popular concepts such as machine learning, deep learning, and neural networks for image processingExplore common and not-so-common challenges faced in image processingBook Description With the advancements in wireless devices and mobile technology, there's increasing demand for people with digital image processing skills in order to extract useful information from the ever-growing volume of images. This book provides comprehensive coverage of the relevant tools and algorithms, and guides you through analysis and visualization for image processing. With the help of over 60 cutting-edge recipes, you'll address common challenges in image processing and learn how to perform complex tasks such as object detection, image segmentation, and image reconstruction using large hybrid datasets. Dedicated sections will also take you through implementing various image enhancement and image restoration techniques, such as cartooning, gradient blending, and sparse dictionary learning. As you advance, you'll get to grips with face morphing and image segmentation techniques. With an emphasis on practical solutions, this book will help you apply deep learning techniques such as transfer learning and fine-tuning to solve real-world problems. By the end of this book, you'll be proficient in utilizing the capabilities of the Python ecosystem to implement various image processing techniques effectively. What you will learnImplement supervised and unsupervised machine learning algorithms for image processingUse deep neural network models for advanced image processing tasksPerform image classification, object detection, and face recognitionApply image segmentation and registration techniques on medical images to assist doctorsUse classical image processing and deep learning methods for image restorationImplement text detection in images using Tesseract, the optical character recognition (OCR) engineUnderstand image enhancement techniques such as gradient blendingWho this book is for This book is for image processing engineers, computer vision engineers, software developers, machine learning engineers, or anyone who wants to become well-versed with image processing techniques and methods using a recipe-based approach. Although no image processing knowledge is expected, prior Python coding experience is necessary to understand key concepts covered in the book.
Astronomical Data Analysis Software And Systems Xiii
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Author : F. Ochsenbein
language : en
Publisher:
Release Date : 2004
Astronomical Data Analysis Software And Systems Xiii written by F. Ochsenbein and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004 with Computers categories.
Modern Python Standard Library Cookbook
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Author : Alessandro Molina
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-08-31
Modern Python Standard Library Cookbook written by Alessandro Molina and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-31 with Computers categories.
Build optimized applications in Python by smartly implementing the standard library Key Features Strategic recipes for effective application development in Python Techniques to create GUIs and implement security through cryptography Best practices for developing readily scalable, production-ready applications Book Description The Python 3 Standard Library is a vast array of modules that you can use for developing various kinds of applications. It contains an exhaustive list of libraries, and this book will help you choose the best one to address specific programming problems in Python. The Modern Python Standard Library Cookbook begins with recipes on containers and data structures and guides you in performing effective text management in Python. You will find Python recipes for command-line operations, networking, filesystems and directories, and concurrent execution. You will learn about Python security essentials in Python and get to grips with various development tools for debugging, benchmarking, inspection, error reporting, and tracing. The book includes recipes to help you create graphical user interfaces for your application. You will learn to work with multimedia components and perform mathematical operations on date and time. The recipes will also show you how to deploy different searching and sorting algorithms on your data. By the end of the book, you will have acquired the skills needed to write clean code in Python and develop applications that meet your needs. What you will learn Store multiple values per key in associative containers Create interactive character-based user interfaces Work with native time and display data for your time zone Read/write SGML family languages, both as a SAX and DOM parser to meet file sizes and other requirements Group equivalent items using itertools and sorted features together Use partials to create unary functions out of multi-argument functions Implement hashing algorithms to store passwords in a safe way Who this book is for If you are a developer who wants to write highly responsive, manageable, scalable, and resilient code in Python, this book is for you. Prior programming knowledge in Python will help you make the most out of the book.
Modern Python Cookbook
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Author : Steven F. Lott
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-07-31
Modern Python Cookbook written by Steven F. Lott and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Computers categories.
Complete recipes spread across 15 chapters to help you overcome commonly faced issues by Python for everybody across the globe. Each recipe takes a problem-solution approach to resolve for effective Python. Key Features Develop expressive and effective Python programs Best practices and common idioms through carefully explained recipes Discover new ways to apply Python for data-focused development Make use of Python’s optional type annotations Book DescriptionPython is the preferred choice of developers, engineers, data scientists, and hobbyists everywhere. It is a great language that can power your applications and provide great speed, safety, and scalability. It can be used for simple scripting or sophisticated web applications. By exposing Python as a series of simple recipes, this book gives you insight into specific language features in a particular context. Having a tangible context helps make the language or a given standard library feature easier to understand. This book comes with 133 recipes on the latest version of Python 3.8. The recipes will benefit everyone, from beginners just starting out with Python to experts. You'll not only learn Python programming concepts but also how to build complex applications. The recipes will touch upon all necessary Python concepts related to data structures, object oriented programming, functional programming, and statistical programming. You will get acquainted with the nuances of Python syntax and how to effectively take advantage of it. By the end of this Python book, you will be equipped with knowledge of testing, web services, configuration, and application integration tips and tricks. You will be armed with the knowledge of how to create applications with flexible logging, powerful configuration, command-line options, automated unit tests, and good documentation.What you will learn See the intricate details of the Python syntax and how to use it to your advantage Improve your coding with Python readability through functions Manipulate data effectively using built-in data structures Get acquainted with advanced programming techniques in Python Equip yourself with functional and statistical programming features Write proper tests to be sure a program works as advertised Integrate application software using Python Who this book is for The Python book is for web developers, programmers, enterprise programmers, engineers, and big data scientists. If you are a beginner, this book will get you started. If you are experienced, it will expand your knowledge base. A basic knowledge of programming would help.