Python Quick Reference Guide

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Python Quick Reference Guide

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Author : JORDAN. LOOPMAN
language : en
Publisher: Independently Published
Release Date : 2025-02-11

Python Quick Reference Guide written by JORDAN. LOOPMAN and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-11 with Computers categories.

Python Quick Reference Guide: The Cheat Sheet for Fast Learning Learn Python's Key Concepts and Boost Your Coding Productivity Struggling to remember Python syntax? Wasting time searching for basic commands? Stop Googling and start coding faster with this ultimate Python cheat sheet! This book is designed for beginners, students, and busy professionals who want a quick, easy-to-use reference guide to Python's most essential features. No fluff, no unnecessary explanations-just straight-to-the-point information to help you code efficiently. What You'll Learn Inside: ✔ Python Essentials - Variables, data types, loops, functions, and more ✔ Built-in Libraries - Master os, random, math, and other must-know modules ✔ Error Handling & Debugging - Fix bugs like a pro ✔ Productivity Hacks - Write cleaner, faster, and more Pythonic code ✔ Advanced Concepts - File handling, object-oriented programming, and automation Why This Book? ✅ Instant Access to Key Python Concepts - Perfect for quick reference ✅ Beginner-Friendly Yet Powerful - Simple explanations with practical examples ✅ Boost Your Coding Productivity - Spend less time stuck, more time building Whether you're learning Python for the first time or need a handy reference for daily coding, this concise, easy-to-follow guide will help you master Python quickly and effectively. ⚡ Get your copy today and start coding smarter! ⚡

Natural Language Processing With Python Quick Start Guide

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Author : Nirant Kasliwal
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30

Natural Language Processing With Python Quick Start Guide written by Nirant Kasliwal 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 2018-11-30 with Computers categories.

Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learning Key FeaturesA no-math, code-driven programmer’s guide to text processing and NLPGet state of the art results with modern tooling across linguistics, text vectors and machine learningFundamentals of NLP methods from spaCy, gensim, scikit-learn and PyTorchBook Description NLP in Python is among the most sought after skills among data scientists. With code and relevant case studies, this book will show how you can use industry-grade tools to implement NLP programs capable of learning from relevant data. We will explore many modern methods ranging from spaCy to word vectors that have reinvented NLP. The book takes you from the basics of NLP to building text processing applications. We start with an introduction to the basic vocabulary along with a workflow for building NLP applications. We use industry-grade NLP tools for cleaning and pre-processing text, automatic question and answer generation using linguistics, text embedding, text classifier, and building a chatbot. With each project, you will learn a new concept of NLP. You will learn about entity recognition, part of speech tagging and dependency parsing for Q and A. We use text embedding for both clustering documents and making chatbots, and then build classifiers using scikit-learn. We conclude by deploying these models as REST APIs with Flask. By the end, you will be confident building NLP applications, and know exactly what to look for when approaching new challenges. What you will learnUnderstand classical linguistics in using English grammar for automatically generating questions and answers from a free text corpusWork with text embedding models for dense number representations of words, subwords and characters in the English language for exploring document clusteringDeep Learning in NLP using PyTorch with a code-driven introduction to PyTorchUsing an NLP project management Framework for estimating timelines and organizing your project into stagesHack and build a simple chatbot application in 30 minutesDeploy an NLP or machine learning application using Flask as RESTFUL APIsWho this book is for Programmers who wish to build systems that can interpret language. Exposure to Python programming is required. Familiarity with NLP or machine learning vocabulary will be helpful, but not mandatory.

Recurrent Neural Networks With Python Quick Start Guide

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Author : Simeon Kostadinov
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-11-30

Recurrent Neural Networks With Python Quick Start Guide written by Simeon Kostadinov 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 2018-11-30 with Computers categories.

Learn how to develop intelligent applications with sequential learning and apply modern methods for language modeling with neural network architectures for deep learning with Python's most popular TensorFlow framework. Key FeaturesTrain and deploy Recurrent Neural Networks using the popular TensorFlow libraryApply long short-term memory unitsExpand your skills in complex neural network and deep learning topicsBook Description Developers struggle to find an easy-to-follow learning resource for implementing Recurrent Neural Network (RNN) models. RNNs are the state-of-the-art model in deep learning for dealing with sequential data. From language translation to generating captions for an image, RNNs are used to continuously improve results. This book will teach you the fundamentals of RNNs, with example applications in Python and the TensorFlow library. The examples are accompanied by the right combination of theoretical knowledge and real-world implementations of concepts to build a solid foundation of neural network modeling. Your journey starts with the simplest RNN model, where you can grasp the fundamentals. The book then builds on this by proposing more advanced and complex algorithms. We use them to explain how a typical state-of-the-art RNN model works. From generating text to building a language translator, we show how some of today's most powerful AI applications work under the hood. After reading the book, you will be confident with the fundamentals of RNNs, and be ready to pursue further study, along with developing skills in this exciting field. What you will learnUse TensorFlow to build RNN modelsUse the correct RNN architecture for a particular machine learning taskCollect and clear the training data for your modelsUse the correct Python libraries for any task during the building phase of your modelOptimize your model for higher accuracyIdentify the differences between multiple models and how you can substitute themLearn the core deep learning fundamentals applicable to any machine learning modelWho this book is for This book is for Machine Learning engineers and data scientists who want to learn about Recurrent Neural Network models with practical use-cases. Exposure to Python programming is required. Previous experience with TensorFlow will be helpful, but not mandatory.

Data Science Quick Reference Manual Analysis And Visualization

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Author : Mario A. B. Capurso
language : en
Publisher: Mario A.B. Capurso
Release Date :

Data Science Quick Reference Manual Analysis And Visualization written by Mario A. B. Capurso and has been published by Mario A.B. Capurso this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. Second of a series of books, it covers methodological aspects, analysis and visualization. It describes the CRISP DM methodology, the working phases, the success criteria, the languages and the environments that can be used, the application libraries. Since this book uses Orange for the application aspects, its installation and widgets are described. In visualization, historical notes are made, and next the book describes the characteristics of an effective visualization, the types of messages that can be conveyed, the Grammar of Graphics, the use of a graph and a dashboard, the software and libraries that can be used, the role and use of color. 55 types of graphs are then analyzed, reporting meaning, use, examples and visual dimensions also with a vocabulary of graphs and summary tables. Examples are given in Orange and the possible use of Python with Orange is explained. Visualization-based inference is discussed, exploratory and confirmatory analysis is defined and techniques are reported. The book is accompanied by supporting material and it is possible to download the project samples in Orange and sample data.

Data Science Quick Reference Manual Methodological Aspects Data Acquisition Management And Cleaning

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Author : Mario A. B. Capurso
language : en
Publisher: Mario Capurso
Release Date :

Data Science Quick Reference Manual Methodological Aspects Data Acquisition Management And Cleaning written by Mario A. B. Capurso and has been published by Mario Capurso this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

This work follows the 2021 curriculum of the Association for Computing Machinery for specialists in Data Sciences, with the aim of producing a manual that collects notions in a simplified form, facilitating a personal training path starting from specialized skills in Computer Science or Mathematics or Statistics. It has a bibliography with links to quality material but freely usable for your own training and contextual practical exercises. First of a series of books, it covers methodological aspects, data acquisition, management and cleaning. It describes the CRISP DM methodology, the working phases, the success criteria, the languages and the environments that can be used, the application libraries. Since this book uses Orange for the application aspects, its installation and widgets are described. Dealing with data acquisition, the book describes data sources, the acceleration techniques, the discretization methods, the security standards, the types and representations of the data, the techniques for managing corpus of texts such as bag-of-words, word-count , TF-IDF, n-grams, lexical analysis, syntactic analysis, semantic analysis, stop word filtering, stemming, techniques for representing and processing images, sampling, filtering, web scraping techniques. Examples are given in Orange. Data quality dimensions are analysed, and then the book considers algorithms for entity identification, truth discovery, rule-based cleaning, missing and repeated value handling, categorical value encoding, outlier cleaning, and errors, inconsistency management, scaling, integration of data from various sources and classification of open sources, application scenarios and the use of databases, datawarehouses, data lakes and mediators, data schema mapping and the role of RDF, OWL and SPARQL, transformations. Examples are given in Orange. The book is accompanied by supporting material and it is possible to download the project samples in Orange and sample data.

Python Made Easy Your Step By Step Guide To Learning Python

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Author : Ayman Elmassarawy
language : en
Publisher: Ayman Elmassarawy
Release Date : 2025-02-08

Python Made Easy Your Step By Step Guide To Learning Python written by Ayman Elmassarawy and has been published by Ayman Elmassarawy this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-08 with Computers categories.

Python has become one of the most widely used and versatile programming languages, known for its simplicity, readability, and power. "Python Made Easy: Your Step-by-Step Guide to Learning Python" is designed to help absolute beginners and aspiring programmers build a solid foundation in Python programming, guiding them from fundamental concepts to real-world applications. This book provides a structured, hands-on approach, breaking down complex topics into clear and digestible lessons. It introduces key programming concepts such as data types, variables, control flow, functions, object-oriented programming, file handling, and working with external libraries. With practical examples, coding exercises, and case studies, readers will gain experience in writing efficient and error-free Python programs. Beyond the basics, this book also covers advanced topics such as debugging techniques, automation, data handling, and command-line arguments, ensuring readers develop a deeper understanding of Python's capabilities. Whether you are interested in automation, web development, data science, or software engineering, this guide equips you with the tools to start coding with confidence. By the end of this book, readers will have not only learned Python syntax and best practices but also developed problem-solving skills essential for real-world programming. With Python Made Easy, learning to code has never been more accessible or engaging. Many beginners find programming intimidating, but Python Made Easy simplifies the learning process with: ✅ Step-by-Step Explanations – Each chapter builds on the previous one, ensuring a smooth learning curve. ✅ Hands-On Exercises – Practical coding exercises help reinforce key concepts. ✅ Real-World Applications – Learn how Python is used in various industries. ✅ Clear and Concise Explanations – Technical concepts are broken down into simple, digestible lessons. ✅ Troubleshooting Tips – Common errors and their solutions are covered throughout the book. Whether you want to automate tasks, build web applications, analyze data, or simply understand how coding works, this book provides the foundational knowledge you need. What You Will Learn: This book is designed to be a complete learning guide for Python beginners. Below is an overview of the topics covered: Introduction to Python and why it is widely used. Chapter 2: Python Basics Chapter 3: Control Flow and Loops Chapter 4: Functions and Modules Chapter 5: Data Structures Chapter 6: Object-Oriented Programming (OOP) Chapter 7: File Handling and Working with Data Chapter 8: Error Handling and Debugging Chapter 9: Working with External Libraries Chapter 10: Building Real-World Python Projects Chapter 11: Next Steps in Python How to Use This Book: This book is structured to be beginner-friendly, but also useful for those with some programming background. You can follow it from start to finish or jump to specific chapters that interest you.

Python Exception Handling Made Easy A Practical Guide With Examples

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Author : William E. Clark
language : en
Publisher: Walzone Press
Release Date : 2025-03-26

Python Exception Handling Made Easy A Practical Guide With Examples written by William E. Clark and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-26 with Computers categories.

This book provides a detailed exploration of error handling in Python with a particular emphasis on practical techniques and clear explanations. It is designed to offer developers a comprehensive guide to understanding and managing exceptions, covering everything from Python’s built-in error types to the implementation of custom exceptions. The text is methodically organized to present a logical progression of concepts, ensuring that readers can build a solid foundation in effective error management. Structured into carefully crafted chapters, the book begins by introducing the fundamental principles of exception handling and the mechanisms used to detect and process errors. It then delves into specific topics such as the nuances of try, except, else, and finally constructs, and the process of creating tailored error responses through custom exception classes. Subsequent sections provide in-depth analysis of debugging strategies, logging best practices, and real-world applications that showcase the integration of robust exception handling into complex Python projects. Intended for both novice and intermediate programmers, this guide is developed to enhance the reliability and maintainability of software through rigorous error management practices. Readers are equipped with not only the theoretical knowledge but also practical examples and exercises that facilitate hands-on learning. The book is a clear and definitive resource for anyone looking to master the art of exception handling in Python and to apply these techniques effectively in their development projects.

Finding Alphas

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Author : Igor Tulchinsky
language : en
Publisher: John Wiley & Sons
Release Date : 2019-10-01

Finding Alphas written by Igor Tulchinsky and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-01 with Business & Economics categories.

Discover the ins and outs of designing predictive trading models Drawing on the expertise of WorldQuant’s global network, this new edition of Finding Alphas: A Quantitative Approach to Building Trading Strategies contains significant changes and updates to the original material, with new and updated data and examples. Nine chapters have been added about alphas – models used to make predictions regarding the prices of financial instruments. The new chapters cover topics including alpha correlation, controlling biases, exchange-traded funds, event-driven investing, index alphas, intraday data in alpha research, intraday trading, machine learning, and the triple axis plan for identifying alphas. • Provides more references to the academic literature • Includes new, high-quality material • Organizes content in a practical and easy-to-follow manner • Adds new alpha examples with formulas and explanations If you’re looking for the latest information on building trading strategies from a quantitative approach, this book has you covered.

Learn Pyqt The Hard Way A Quick Start Guide To Postgresql And Sqlite Driven Programming

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Author : Vivian Siahaan
language : en
Publisher: SPARTA PUBLISHING
Release Date : 2019-11-25

Learn Pyqt The Hard Way A Quick Start Guide To Postgresql And Sqlite Driven Programming written by Vivian Siahaan and has been published by SPARTA PUBLISHING this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-25 with Computers categories.

This book explains relational theory in practice, and demonstrates through two projects how you can apply it to your use of PostgreSQL and SQLite databases. This book covers the important requirements of teaching databases with a practical and progressive perspective. This book offers the straightforward, practical answers you need to help you do your job. This hands-on tutorial/reference/guide to PostgreSQL and SQLite is not only perfect for students and beginners, but it also works for experienced developers who aren't getting the most from both databases. In designing a GUI and as an IDE, you will make use Qt Designer. In the first chapter, you will learn to use several widgets in PyQt5: Display a welcome message; Use the Radio Button widget; Grouping radio buttons; Displays options in the form of a check box; and Display two groups of check boxes. In chapter two, you will learn to use the following topics: Using Signal / Slot Editor; Copy and place text from one Line Edit widget to another; Convert data types and make a simple calculator; Use the Spin Box widget; Use scrollbars and sliders; Using the Widget List; Select a number of list items from one Widget List and display them on another Widget List widget; Add items to the Widget List; Perform operations on the Widget List; Use the Combo Box widget; Displays data selected by the user from the Calendar Widget; Creating a hotel reservation application; and Display tabular data using Table Widgets. In chapter three, you will learn: How to create the initial three tables project in the School database: Teacher, Class, and Subject tables; How to create database configuration files; How to create a Python GUI for inserting and editing tables; How to create a Python GUI to join and query the three tables. In chapter four, you will learn how to: Create a main form to connect all forms; Create a project will add three more tables to the school database: Student, Parent, and Tuition tables; Create a Python GUI for inserting and editing tables; Create a Python GUI to join and query over the three tables. In chapter five, you will join the six classes, Teacher, TClass, Subject, Student, Parent, and Tuition and make queries over those tables. In chapter six and chapter seven, you will get introduction of postgresql. And then, you will learn querying data from the postgresql using Python including establishing a database connection, creating a statement object, executing the query, processing the resultset object, querying data using a statement that returns multiple rows, querying data using a statement that has parameters, inserting data into a table using Python, updating data in postgresql database using Python, calling postgresql stored function using Python, deleting data from a postgresql table using Python, and postgresql Python transaction. In chapter eight, you will create dan configure PotgreSQL database. In this chapter, you will create Suspect table in crime database. This table has eleven columns: suspect_id (primary key), suspect_name, birth_date, case_date, report_date, suspect_ status, arrest_date, mother_name, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for this table. In chapter nine, you will create a table with the name Feature_Extraction, which has eight columns: feature_id (primary key), suspect_id (foreign key), feature1, feature2, feature3, feature4, feature5, and feature6. The six fields (except keys) will have a VARCHAR data type (200). You will also create GUI to display, edit, insert, and delete for this table. In chapter ten, you will create two tables, Police and Investigator. The Police table has six columns: police_id (primary key), province, city, address, telephone, and photo. The Investigator table has eight columns: investigator_id (primary key), investigator_name, rank, birth_date, gender, address, telephone, and photo. You will also create GUI to display, edit, insert, and delete for both tables. In chapter eleven, you will create two tables, Victim and Case_File. The Victim table has nine columns: victim_id (primary key), victim_name, crime_type, birth_date, crime_date, gender, address, telephone, and photo. The Case_File table has seven columns: case_file_id (primary key), suspect_id (foreign key), police_id (foreign key), investigator_id (foreign key), victim_id (foreign key), status, and description. You will create GUI to display, edit, insert, and delete for both tables as well.

Python For Dummies

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Author : Stef Maruch
language : en
Publisher: John Wiley & Sons
Release Date : 2006-09-14

Python For Dummies written by Stef Maruch and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-09-14 with Computers categories.

Python is one of the most powerful, easy-to-read programming languages around, but it does have its limitations. This general purpose, high-level language that can be extended and embedded is a smart option for many programming problems, but a poor solution to others. Python For Dummies is the quick-and-easy guide to getting the most out of this robust program. This hands-on book will show you everything you need to know about building programs, debugging code, and simplifying development, as well as defining what actions it can perform. You’ll wrap yourself around all of its advanced features and become an expert Python user in no time. This guide gives you the tools you need to: Master basic elements and syntax Document, design, and debug programs Work with strings like a pro Direct a program with control structures Integrate integers, complex numbers, and modules Build lists, stacks, and queues Create an organized dictionary Handle functions, data, and namespace Construct applications with modules and packages Call, create, extend, and override classes Access the Internet to enhance your library Understand the new features of Python 2.5 Packed with critical idioms and great resources to maximize your productivity, Python For Dummies is the ultimate one-stop information guide. In a matter of minutes you’ll be familiar with Python’s building blocks, strings, dictionaries, and sets; and be on your way to writing the program that you’ve dreamed about!