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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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Quick Python 3
Are you a programmer who wants to get started quickly in a new language? This book is for you.Are you a novice who wants to learn to program? This book is not for you. Are you a Python programmer who needs encyclopaedic information? This book is not for you.Like any mainstream language, Python has loops, if statements, assignment statements, functions, etc. I’ll show you what these look like in Python. I won’t waste your time telling you what they’re good for. Python has features you may not be familiar with--iterators, list comprehensions, maybe even dictionaries. I’ll spend more time on these. I’ll cover some of the library functions I found most immediately useful, and tell you where to find more. In short, this book will help you hit the ground running. Next week, you’ll be ready to buy that Python encyclopaedia.
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Esri Advanced Guide to Python in ArcGIS
Solving complex geospatial problems and delivering solutions has never been easier.Ready to take your Python knowledge to the next level? Esri Advanced Guide to Python in ArcGIS guides working GIS professionals through integrating Python with ArcGIS capabilities with increasing complexity through each consecutive chapter. Every chapter includes a project that teaches technical skills and problem-solving applicable to practical, job-focused assignments, including understanding client needs, performing market analytics, and managing ArcGIS Online organizations. Esri Advanced Guide to Python in ArcGIS uses step-by-step tutorials with an informal, conversational style of writing so you can easily follow and immediately apply the skills explained. Topics include: Designing effective GIS Python solutions ArcPy and ArcGIS API for Python basics Using imagery and GeoAI for advanced analysis Object-oriented programming Delivering work in various formats: Python scripts, Jupyter Notebook, ArcGIS Pro tools, geoprocessing services, and web applications Data engineering and manipulation techniques Managing ArcGIS Enterprise, ArcGIS Online, and other portal administration Perfect for intermediate to advanced programmers looking to enhance their GIS capabilities, Esri Advanced Guide to Python in ArcGIS will quickly help you become skilled at using Python for geospatial solutions and become more proficient and capable in your work.
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Maya Python for Games and Film
Maya Python for Games and Film is the first book to focus exclusively on how to implement Python with Maya. Written by trusted authorities in the field, this in-depth guide will help you master Maya Python, whether you're a seasoned technical artist looking to make the transition from MEL to Python or an aspiring artist not wanting to scramble for information.
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Expert Python Programming -
Become an ace Python programmer by learning best coding practices and advance-level concepts with Python 3.5About This Book• Based on the latest stable version of Python (version 3.5)• Creating well manageable code that will run in various environments with different sets of dependencies• Packed with advanced concepts and best practices to write efficient Python codeWho This Book Is ForThe book would appeal to web developers and Python programmers who want to start using version 3.5 and write code efficiently. Basic knowledge of Python programming is expected.What You Will Learn• Conventions and best practices that are widely adopted in the python community• Package python code effectively for community and production use• Easy and lightweight ways to automate code deployment on remote systems• Improve your code's quality, reliability, and performance• Write concurrent code in python• Extend python with code written in different languagesIn DetailPython is a dynamic programming language, used in a wide range of domains by programmers who find it simple, yet powerful. Even if you find writing Python code easy, writing code that is efficient and easy to maintain and reuse is a challenge.The focus of the book is to familiarize you with common conventions, best practices, useful tools and standards used by python professionals on a daily basis when working with code.You will begin with knowing new features in Python 3.5 and quick tricks for improving productivity. Next, you will learn advanced and useful python syntax elements brought to this new version. Using advanced object-oriented concepts and mechanisms available in python, you will learn different approaches to implement metaprogramming. You will learn to choose good names, write packages, and create standalone executables easily.You will also be using some powerful tools such as buildout and vitualenv to release and deploy the code on remote servers for production use. Moving on, you will learn to effectively create Python extensions with C, C++, cython, and pyrex. The important factors while writing code such as code management tools, writing clear documentation, and test-driven development are also covered.You will now dive deeper to make your code efficient with general rules of optimization, strategies for finding bottlenecks, and selected tools for application optimization.By the end of the book, you will be an expert in writing efficient and maintainable code.Style and approach An easy-to-follow guide that covers industry followed best practices in Python programming
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Advanced Python Development
This book builds on basic Python tutorials to explain various Python language features that aren’t routinely covered: from reusable console scripts that play double duty as micro-services by leveraging entry points, to using asyncio efficiently to collate data from a large number of sources. Along the way, it covers type-hint based linting, low-overhead testing and other automated quality checking to demonstrate a robust real-world development process.Some powerful aspects of Python are often documented with contrived examples that explain the feature as a standalone example only. By following the design and build of a real-world application example from prototype to production quality you'll see not only how the various pieces of functionality work but how they integrate as part of the larger system design process. In addition, you'll benefit from the kind of useful asides and library recommendations that are a staple of conference Q&A sessions at Python conferences as well as discussions of modern Python best practice and techniques to better produce clear code that is easily maintainable.Advanced Python Development is intended for developers who can already write simple programs in Python and want to understand when it’s appropriate to use new and advanced language features and to do so in a confident manner. It is especially of use to developers looking to progress to a more senior level and to very experienced developers who have thus far used older versions of Python.What You'll Learn Understand asynchronous programmingExamine developing plugin architecturesWork with type annotationsReview testing techniquesExplore packaging and dependency managementWho This Book Is ForDevelopers at the mid to senior level who already have Python experience.
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Functional Python Programming
Python isn't all about object-oriented programming. Discover a valuable way of thinking about code design through a function-first approach – and learn when you need to use it. Now with detailed exercises at the end of every chapter!Purchase of the print or Kindle book includes a free eBook in PDF format.Key FeaturesLearn how, when, and why to adopt functional elements in your projectsExplore the Python modules essential to functional programming, like itertools and functoolsRevised to cover new features of Python 3.10, exercises at the end of every chapter, and moreBook DescriptionNot enough developers understand the benefits of functional programming, or even what it is. Author Steven Lott demystifies the approach, teaching you how to improve the way you code in Python and make gains in memory use and performance. Starting from the fundamentals, this book shows you how to apply functional thinking and techniques in a range of scenarios, with examples centered around data cleaning and exploratory data analysis. You'll learn how to use generator expressions, list comprehensions, and decorators to your advantage. You don't have to abandon object-oriented design completely, though – you'll also see how Python's native object-orientation is used in conjunction with functional programming techniques. By the end of this book, you'll be well versed in the essential functional programming features of Python, and understand why and when functional thinking helps. You'll also have all the tools you need to pursue any additional functional topics that are not part of the Python language.What you will learnUse Python's libraries to avoid the complexities of state-changing classesLeverage built-in higher-order functions to avoid rewriting common algorithmsWrite generator functions to create lazy processingDesign and implement decorators for functional compositionMake use of Python type annotations to describe parameters and results of functionsApply functional programming to concurrency and web servicesExplore the PyMonad library for stateful simulationsWho this book is forThe functional paradigm is very useful for programmers working in data science, but any Python developer who wants to create more reliable, succinct, and expressive code will have much to learn from this book.No prior knowledge of functional programming is required to get started, though Python programming knowledge is assumed. A running Python environment is essential.
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Python 3 Using DeepSeek
This book is your definitive guide to mastering DeepSeek, a leading open-source Large Language Model (LLM), and leveraging its power through practical Python programming. It is structured to build your expertise from foundational Python data structures and object-oriented programming to advanced model deployment.The initial chapters establish a strong technical base in Python's core features, including comprehensions, iterators, and the OOP paradigm. The focus then shifts entirely to DeepSeek, detailing its innovative Mixture-of-Experts (MoE) architecture, its superior performance on code-centric benchmarks like HumanEval, and its efficiency advantages. You will gain crucial insight into model management, specifically through the concept of quantization and local deployment with tools like Ollama, which is essential for maximizing performance while minimizing resource usage. The final chapter provides numerous, practical Python mini-projects, allowing you to immediately apply DeepSeek's capabilities to a range of real-world tasks from basic web scraping and data visualization to advanced object-oriented programming and linear regression.Python 3 Using DeepSeek is essential reading for Python developers (intermediate to advanced), machine learning practitioners, and data scientists. It is your guide to integrating high-performing, open-source LLMs into your workflows, particularly for code generation, algorithmic reasoning, and highly efficient local model deployment.
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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 Automation Cookbook
Step-by-step instructions which take you through each program to automate monotonous tasks with Python 3.7Key FeaturesAutomate integral business processes such as report generation, email marketing, and lead generationBuild your first web application that scrapes data and accesses websites' APIsCreate graphic-rich charts, graphs, and maps using MatplotlibBook DescriptionHave you been doing the same old monotonous office work over and over again? Or have you been trying to find an easy way to make your life better by automating some of your repetitive tasks? Through a tried and tested approach, understand how to automate all the boring stuff using Python. The Python Automation Cookbook helps you develop a clear understanding of how to automate your business processes using Python, including detecting opportunities by scraping the web, analyzing information to generate automatic spreadsheets reports with graphs, and communicating with automatically generated emails. You’ll learn how to get notifications via text messages and run tasks while your mind is focused on other important activities, followed by understanding how to scan documents such as résumés. Once you’ve gotten familiar with the fundamentals, you’ll be introduced to the world of graphs, along with studying how to produce organized charts using Matplotlib. In addition to this, you’ll gain in-depth knowledge of how to generate rich graphics showing relevant information. By the end of this book, you’ll have refined your skills by attaining a sound understanding of how to identify and correct problems to produce superior and reliable systems.What you will learnGet to grips with scraping a website to detect changesSearch and process raw sales files to aggregate information in spreadsheetsExplore techniques to extract information from an Excel spreadsheet and generate exciting reports with graphsDiscover the techniques required to generate random, print-friendly codes to be used as single-use couponsAutomatically generate a marketing campaign, contacting the recipients over different channelsIdentify and implement precise solutionsWho this book is forThe Python Automation Cookbook is for you if you are a developer or anyone who wants to automate monotonous manual tasks related to fields such as finance, sales, and HR, among others.
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Learn Programming in Python with Cody Jackson
Kick-start your development journey with this end-to-end guide that covers Python programming fundamentals along with application developmentKey FeaturesGain a solid understanding of Python programming with coverage of data structures and Object-Oriented Programming (OOP)Design graphical user interfaces for desktops with libraries such as Kivy and TkinterWrite elegant, reusable, and efficient code Book DescriptionPython is a cross-platform language used by organizations such as Google and NASA. It lets you work quickly and efficiently, allowing you to concentrate on your work rather than the language. Based on his personal experiences when learning to program, Learn Programming in Python with Cody Jackson provides a hands-on introduction to computer programming utilizing one of the most readable programming languages–Python. It aims to educate readers regarding software development as well as help experienced developers become familiar with the Python language, utilizing real-world lessons to help readers understand programming concepts quickly and easily. The book starts with the basics of programming, and describes Python syntax while developing the skills to make complete programs. In the first part of the book, readers will be going through all the concepts with short and easy-to-understand code samples that will prepare them for the comprehensive application built in parts 2 and 3. The second part of the book will explore topics such as application requirements, building the application, testing, and documentation. It is here that you will get a solid understanding of building an end-to-end application in Python. The next part will show you how to complete your applications by converting text-based simulation into an interactive, graphical user interface, using a desktop GUI framework. After reading the book, you will be confident in developing a complete application in Python, from program design to documentation to deployment.What you will learnUse the interactive shell for prototyping and code execution, including variable assignment Deal with program errors by learning when to manually throw exceptions Employ exceptions for code management Enhance code by utilizing Python's built-in shortcuts to improve efficiency and make coding easier Interact with files and package Python data for network transfer or storage Understand how tests drive code writing, and vice versaExplore the different frameworks that are available for GUI developmentWho this book is forLearn Programming in Python with Cody Jackson is for beginners or novice programmers who have no programming background and wish to take their first step in software development. This book will also be beneficial for intermediate programmers and will provide deeper insights into effective coding practices in Python.
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Introduction To Time-dependent Quantum Mechanics With Python
Computational spectroscopy and computational quantum chemical dynamics is a vast field in physical chemistry. Significant part of this field is developed based on the concepts of time-dependent quantum mechanics and its numerical implementations.This book gives an introduction to the Time-Dependent Quantum Chemistry for use with any introductory college/university course in optics, spectroscopy, kinetics, dynamics, or experimental physical chemistry or chemical physics of the kind usually taken by undergraduate and graduate students in physical chemistry. In this book, different concepts of time-dependent quantum mechanics are systematically presented by first giving emphasis on the contrasting viewpoint of classical and quantum mechanical motion of a particle, then by demonstrating the ways to find classical flavour in quantum dynamics, thereafter by formally defining the wavepacket which represents a quantum particle and finally by demonstrating numerical methods to explore the wavepacket dynamics in one dimension. Along with the analytical theory, accompanying Python chapters in this book take readers to a hands-on tour with Python programming by first giving them a quick introduction to the Python programming, then by introducing the position-space grid representation of the wavefunction, thereafter, by making them familiarized with the Fourier transform to represent the discretized wavefunction in momentum space, subsequently by showing the Python-based methodologies to express Hamiltonian operator in matrix form and finally by demonstrating the entire Python program which solves the wavepacket dynamics in one dimension under influence of time-independent Hamiltonian following split-operator approach.Rigorous class-testing of the presented lecture notes at the Indian Institute of Science, GITAM University and at NPTEL platform reveals that physical chemistry students, after thoroughly going through all chapters, not only develop an in-depth understanding of the wavepacket dynamics and its numerical implementations, but also start successfully writing their own Python code for solving any one dimensional wavepacket dynamics problem.
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