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Mathematical Logic through Python
Using a unique pedagogical approach, this text introduces mathematical logic by guiding students in implementing the underlying logical concepts and mathematical proofs via Python programming. This approach, tailored to the unique intuitions and strengths of the ever-growing population of programming-savvy students, brings mathematical logic into the comfort zone of these students and provides clarity that can only be achieved by a deep hands-on understanding and the satisfaction of having created working code. While the approach is unique, the text follows the same set of topics typically covered in a one-semester undergraduate course, including propositional logic and first-order predicate logic, culminating in a proof of Gödel's completeness theorem. A sneak peek to Gödel's incompleteness theorem is also provided. The textbook is accompanied by an extensive collection of programming tasks, code skeletons, and unit tests. Familiarity with proofs and basic proficiency in Python is assumed.
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Learn Enough Python to Be Dangerous
All You Need to Know, and Nothing You Don't, to Solve Real Problems with Python Python is the dominant programming language for data science and an ideal first programming language for web development and many other uses. You should learn Python, but you don't need to learn "everything" to get started, just how to use it efficiently to solve real problems. In Learn Enough Python to Be Dangerous, renowned instructor Michael Hartl teaches the specific concepts, skills, and approaches you need to be professionally productive. Even if you've never programmed before, Hartl helps you quickly build technical sophistication and master the lore you need to succeed. Hartl introduces Python both as a general-purpose language and as a specialist tool for web development and data science, presenting focused examples and exercises that help you internalize what matters, without wasting time on details pros don't care about. Soon, it'll be like you were born knowing this stuff--and you'll be suddenly, seriously dangerous. Learn enough about . . . Applying core Python concepts with the interactive interpreter and command lineWriting object-oriented code with Python's native objectsDeveloping and publishing self-contained Python packagesUsing elegant, powerful functional programming techniquesBuilding new objects, and extending them via Test-Driven Development (TDD)Leveraging Python's exceptional shell scripting capabilitiesCreating and deploying a full web app, using routes, layouts, embedded Python, and formsGetting started with data science tools for calculation, visualization, analysis, and machine learningMastering concrete and informal skills every developer needs Like this book? Don't miss Michael Hartl's companion video tutorial, Learn Enough Python to Be Dangerous LiveLessons. Michael Hartl's Learn Enough Series includes books and video courses that focus on the most important parts of each subject, so you don't have to learn everything to get started--you just have to learn enough to be dangerous and solve technical problems yourself.
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Python Automation For Dummies
Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.
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Classic Computer Science Problems in Python
Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means. Classic Computer Science Problems in Python deepens your Python language skills by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you'll remember important things you've forgotten and discover classic solutions to your "new" problems Key Features · Breadth-first and depth-first search algorithms · Constraints satisfaction problems · Common techniques for graphs · Adversarial Search · Neural networks and genetic algorithms · Written for data engineers and scientists with experience using Python. For readers comfortable with the basics of Python About the technology Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and you’ll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges you’ll face as you grow your skill as a programmer. David Kopec teaches at Champlain College in Burlington, VT and is the author of Manning’s Classic Computer Science Problemsin Swift.
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Python Real-World Projects
Develop Python applications using an enterprise approach with unit and acceptance tests, following agile methodologies to create a minimally viable product and iteratively adding features.Key FeaturesBuild two dozen projects to demonstrate mastery of Python and related technologiesBuild a personal project portfolio that can be an important adjunct to a resume or CVLearn about data acquisition, preparation, and analysis applicationsBook DescriptionIn today's job market, a project portfolio often outshines a traditional resume for developers. This guide empowers you to grasp crucial Python concepts while building complete modules and applications that resonate in real-world scenarios. With two dozen meticulously designed projects, showcase your Python mastery and refine your skills further.Tailored for those with a foundational understanding of class definitions, module creation, and Python's inherent data structures, this book is your gateway to programming excellence. Harness both the standard library and key external projects like Jupyter Lab, pydantic, pytest, and requests. Embrace an enterprise-oriented methodology, including unit and acceptance testing, and an agile development approach. Dive into the software development lifecycle, starting with a minimum viable product and seamlessly expanding it to add innovative features.Whether you're a developer with a working knowledge of Python programming, looking for projects to demonstrate their skills or a developer who want more background in building complete applications that include comprehensive test cases and documentation. his book's practical approach empowers you to craft deployable projects that exhibit your Python proficiency, paving the way for a successful career.What you will learnCore deliverables for an application including documentation and test casesSome approaches to data acquisition including file processing, RESTful APIs, and SQL queriesCreating a data inspection notebook to establish properties of source dataWriting applications to validate, clean, convert, and normalize source dataUse some foundational graphical analysis techniques to visualize dataBuild basic univariate and multivariate statistical analysis toolsCreate reports from raw data using Jupyter Lab publication toolsWho this book is forBeginner to Intermediate level Python Programmers. It is an outright projects book and it assumes the reader to understand basic programming concepts which they have studied during the college times and basic Python understanding like Syntax and writing simple programs. Rest of the book can be interactive project. People knowing programing and seeking jobs can be an ideal readers of the book.
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Natural Language Processing with Python Quick Start Guide
Build and deploy intelligent applications for natural language processing with Python by using industry standard tools and recently popular methods in deep learningKey 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 DescriptionNLP 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 forProgrammers 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.
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Python for Software Design
A no-nonsense introduction to software design using the Python programming language. Written for people with no programming experience, this book starts with the most basic concepts and gradually adds new material. Some of the ideas students find most challenging, like recursion and object-oriented programming, are divided into a sequence of smaller steps and introduced over the course of several chapters. The focus is on the programming process, with special emphasis on debugging. The book includes a wide range of exercises, from short examples to substantial projects, so that students have ample opportunity to practise each new concept. Exercise solutions and code examples are available from thinkpython.com, along with Swampy, a suite of Python programs that is used in some of the exercises.
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Mastering Python Scripting for System Administrators
Leverage the features and libraries of Python to administrate your environment efficiently.Key FeaturesLearn how to solve problems of system administrators and automate routine activitiesLearn to handle regular expressions, network administration Building GUI, web-scraping and database administration including data analyticsBook DescriptionPython has evolved over time and extended its features in relation to every possible IT operation. Python is simple to learn, yet has powerful libraries that can be used to build powerful Python scripts for solving real-world problems and automating administrators' routine activities. The objective of this book is to walk through a series of projects that will teach readers Python scripting with each project.This book will initially cover Python installation and quickly revise basic to advanced programming fundamentals. The book will then focus on the development process as a whole, from setup to planning to building different tools. It will include IT administrators' routine activities (text processing, regular expressions, file archiving, and encryption), network administration (socket programming, email handling, the remote controlling of devices using telnet/ssh, and protocols such as SNMP/DHCP), building graphical user interface, working with websites (Apache log file processing, SOAP and REST APIs communication, and web scraping), and database administration (MySQL and similar database data administration, data analytics, and reporting).By the end of this book, you will be able to use the latest features of Python and be able to build powerful tools that will solve challenging, real-world tasksWhat you will learnUnderstand how to install Python and debug Python scriptsUnderstand and write scripts for automating testing and routine administrative activitiesUnderstand how to write scripts for text processing, encryption, decryption, and archivingHandle files, such as pdf, excel, csv, and txt files, and generate reportsWrite scripts for remote network administration, including handling emailsBuild interactive tools using a graphical user interfaceHandle Apache log files, SOAP and REST APIs communicationAutomate database administration and perform statistical analysisWho this book is forThis book would be ideal for users with some basic understanding of Python programming and who are interested in scaling their programming skills to command line scripting and system administration. Prior knowledge of Python would be necessary.
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