Author: Diego Rodrigues
Publisher: Diego Rodrigues
ISBN:
Category : Computers
Languages : en
Pages : 294

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Book Description
🚀 TAKE ADVANTAGE OF THE PROMOTIONAL LAUNCH PRICE OF THE YEAR 🚀 Become a Python expert with "40 Python Libraries: An Essential Guide for Students and Professionals - 2024 Edition". This guide by Diego Rodrigues is a must-have for students, developers, and professionals who want to master Python and its practical applications. Dive into the Python ecosystem by exploring powerful libraries. Use NumPy for scientific computing, Pandas for data analysis, Matplotlib and Seaborn for visualization, Scikit-learn for machine learning, TensorFlow and Keras for deep learning. Web development becomes easy with Flask and Django, while Requests and BeautifulSoup simplify web scraping. Enhance computer vision skills with OpenCV and Pillow, and develop games with PyGame. Discover SciPy for scientific computing and SymPy for symbolic mathematics. Use Statsmodels for data analysis and visualize interactively with Plotly and Bokeh. Explore NLP with NLTK and spaCy, neural networks with PyTorch, graph analysis with NetworkX, and data mining with Scrapy. SQLAlchemy optimizes databases, Celery for parallel processing, and PandasQL integrates SQL with DataFrames. Handle big data with Dask, test software with PyTest, and use Jupyter for interactive notebooks. Leverage Hadoop and Spark for Big Data, and Kivy and Tkinter for graphical interfaces. Apply these libraries to practical projects: analyzing large datasets, building predictive models, developing web and mobile applications, automating tasks, and integrating with platforms like AWS, Google Cloud, and Microsoft Azure. With this book, acquire the skills to innovate and lead in the competitive tech world, tackling challenges efficiently. Transform your skills into a strategic advantage. This practical, results-focused book accelerates your learning and boosts your career. Get your copy and start mastering Python and its libraries, turning challenges into effective solutions. Python programming, scientific computing, data analysis, visualization, machine learning, artificial intelligence, neural networks, automation, web development, cybersecurity, big data, software engineering, computer science, statistical analysis, data mining, machine learning, deep learning, web frameworks, RESTful APIs, cloud computing, technological innovation, operational efficiency, data science, computer vision, natural language processing, IoT, cloud security, DevOps, predictive analytics, Docker, Kubernetes, Hadoop, Spark, SQL, NoSQL, sentiment analysis, A/B testing, predictive modeling, systems design, prototyping, SCRUM, Agile, project management, business analysis. Tags: Python NumPy Pandas Matplotlib Seaborn Scikit-learn TensorFlow Keras Flask Django Requests BeautifulSoup OpenCV Pillow PyGame SciPy SymPy Statsmodels Plotly Bokeh NLTK spaCy PyTorch NetworkX Scrapy SQLAlchemy Celery PandasQL Dask PyTest Jupyter Hadoop Spark Kivy Tkinter automation scientific computing data visualization artificial intelligence neural networks machine learning deep learning big data data analysis computer science software engineering cybersecurity AWS Google Cloud Microsoft Azure RESTful APIs Python programming technological innovation operational efficiency computer vision natural language processing IoT cloud security DevOps predictive analytics Docker Kubernetes SQL NoSQL sentiment analysis A/B testing predictive modeling systems design prototyping SCRUM Agile project management business analysis Diego Rodrigues

Author: Eric Matthes
Publisher: No Starch Press
ISBN: 1718502702
Category : Computers
Languages : en
Pages : 553

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Book Description
Python Crash Course is the world’s bestselling programming book, with over 1,500,000 copies sold to date! Python Crash Course is the world’s best-selling guide to the Python programming language. This fast-paced, thorough introduction will have you writing programs, solving problems, and developing functioning applications in no time. You’ll start by learning basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You’ll also learn how to make your programs interactive and test your code safely before adding it to a project. You’ll put your new knowledge into practice by creating a Space Invaders–inspired arcade game, building a set of data visualizations with Python’s handy libraries, and deploying a simple application online. As you work through the book, you’ll learn how to: Use powerful Python libraries and tools, including pytest, Pygame, Matplotlib, Plotly, and Django Make increasingly complex 2D games that respond to keypresses and mouse clicks Generate interactive data visualizations using a variety of datasets Build apps that allow users to create accounts and manage their own data, and deploy your apps online Troubleshoot coding errors and solve common programming problems New to this edition: This third edition is completely revised to reflect the latest in Python code. New and updated coverage includes VS Code for text editing, the pathlib module for file handling, pytest for testing your code, as well as the latest features of Matplotlib, Plotly, and Django. If you’ve been thinking about digging into programming, Python Crash Course will provide you with the skills to write real programs fast. Why wait any longer? Start your engines and code! Uses Python 3

Author: Joannah Nanjekye
Publisher: Apress
ISBN: 148422955X
Category : Computers
Languages : en
Pages : 149

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Book Description
Discover clean ways to write code that will run on both Python 2 and 3.This book is tutorial-oriented with detailed examples of how to convert existing Python 2-compatible code to code that will run reliably on both Python 2 and 3. Although Python 3 is considered the future of Python, Python 2.x will be maintained for several more years, alongside Python 3, which is not backwards compatible. For those who need to support both versions, this book guides you through the process. Python 2 and 3 Compatibility explains the syntactical differences between Python 2 and 3, and how to use Python packages Python-Future and Six to implement neutral compatibility. Developers working on either small, medium, or large projects will appreciate the author's clear explanations, detailed examples, and clean techniques to help them extend support for both versions to their existing Python 2-compatible projects. What You'll Learn Understand the syntactical differences between Python 2 and 3 Use the Six and Future libraries Review the new features in Python 3 Choose which Python versions to support when doing neutral support Decide on whether to port or provide support for both versions Who This Book Is For Professional Python developers and enthusiasts that want to implement Python 3 support for their existing Python 2 compatible code.

Author: Shivakumar Gopalakrishnan
Publisher: BPB Publications
ISBN: 936589431X
Category : Computers
Languages : en
Pages : 437

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Book Description
DESCRIPTION Modern Python Programming using ChatGPT is your essential guide to leveraging Artificial Intelligence to streamline and enhance your Python development workflow across the entire software development lifecycle (SDLC). This book covers every stage, from requirements gathering and design to implementation, testing, security, deployment, and observability, demonstrating how ChatGPT can be of invaluable assistance throughout. Learn how to use ChatGPT to break down features into stories, design, and architect software, implement AI-generated code snippets, write clean and maintainable code, test and secure applications, deploy efficiently, and monitor performance. This comprehensive guide shows you how to integrate ChatGPT seamlessly into every stage of your Python projects. Discover how ChatGPT can automate repetitive tasks, generate high-quality code snippets, provide instant debugging tips, and ensure your code adheres to industry standards and best practices. This book provides thorough coverage of the latest trends and best practices in Python development, equipping you with the tools to write clean, maintainable, and robust code. Through practical examples and hands-on exercises, you will learn how to apply ChatGPT in real-world scenarios, making your development process more efficient and productive. KEY FEATURES ● Supercharge the entire SDLC using ChatGPT's AI-driven insights. ● Seamlessly integrate ChatGPT into every stage of your Python projects. ● Practical, real-world examples and hands-on exercises. WHAT YOU WILL LEARN ● To seamlessly integrate ChatGPT from coding to deployment to monitoring. ● Use ChatGPT to gather and document software requirements. ● Break down features into stories with ChatGPT assistance. ● Design, architect, and implement clean, maintainable code using AI-generated snippets. ● Test, secure, and deploy applications with AI support. ● Optimize performance and monitor software using ChatGPT. WHO THIS BOOK IS FOR This book is for Python developers of all experience levels who want to enhance their entire software development process using AI. Basic knowledge of Python is assumed, but detailed instructions are provided to help you integrate ChatGPT into your projects effectively. TABLE OF CONTENTS 1. ChatGPT and Its Capabilities 2. Benefits of Using ChatGPT in Python Development 3. Setting up ChatGPT for Python Development 4. Requirements Gathering 5. Design and Architecture 6. Implementing a Software Product 7. Pull Review and Commit Messages 8. Using ChatGPT for Coding with SOLID Principles 9. Software Testing with ChatGPT in Python 10. Deployment with ChatGPT 11. Performance and Observability 12. Revolutionary Impact of ChatGPT 13. Limitations, Pitfalls and Dangers of ChatGPT 14. Preparing for the Future with ChatGPT

Author: Mark Lutz
Publisher: "O'Reilly Media, Inc."
ISBN: 0596554494
Category : Computers
Languages : en
Pages : 749

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Book Description
Portable, powerful, and a breeze to use, Python is ideal for both standalone programs and scripting applications. With this hands-on book, you can master the fundamentals of the core Python language quickly and efficiently, whether you're new to programming or just new to Python. Once you finish, you will know enough about the language to use it in any application domain you choose. Learning Python is based on material from author Mark Lutz's popular training courses, which he's taught over the past decade. Each chapter is a self-contained lesson that helps you thoroughly understand a key component of Python before you continue. Along with plenty of annotated examples, illustrations, and chapter summaries, every chapter also contains Brain Builder, a unique section with practical exercises and review quizzes that let you practice new skills and test your understanding as you go. This book covers: Types and Operations -- Python's major built-in object types in depth: numbers, lists, dictionaries, and more Statements and Syntax -- the code you type to create and process objects in Python, along with Python's general syntax model Functions -- Python's basic procedural tool for structuring and reusing code Modules -- packages of statements, functions, and other tools organized into larger components Classes and OOP -- Python's optional object-oriented programming tool for structuring code for customization and reuse Exceptions and Tools -- exception handling model and statements, plus a look at development tools for writing larger programs Learning Python gives you a deep and complete understanding of the language that will help you comprehend any application-level examples of Python that you later encounter. If you're ready to discover what Google and YouTube see in Python, this book is the best way to get started.

Author: Sulekha Aloorravi
Publisher: Orange Education Pvt Ltd
ISBN: 8196815107
Category : Computers
Languages : en
Pages : 311

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Book Description
Decode the language of time with Python. Discover powerful techniques to analyze, forecast, and innovate. Key Features ● Dive into time series analysis fundamentals, progressing to advanced Python techniques. ● Gain practical expertise with real-world datasets and hands-on examples. ● Strengthen skills with code snippets, exercises, and projects for deeper understanding. Book Description "Mastering Time Series Analysis and Forecasting with Python" is an essential handbook tailored for those seeking to harness the power of time series data in their work. The book begins with foundational concepts and seamlessly guides readers through Python libraries such as Pandas, NumPy, and Plotly for effective data manipulation, visualization, and exploration. Offering pragmatic insights, it enables adept visualization, pattern recognition, and anomaly detection. Advanced discussions cover feature engineering and a spectrum of forecasting methodologies, including machine learning and deep learning techniques such as ARIMA, LSTM, and CNN. Additionally, the book covers multivariate and multiple time series forecasting, providing readers with a comprehensive understanding of advanced modeling techniques and their applications across diverse domains. Readers develop expertise in crafting precise predictive models and addressing real-world complexities. Complete with illustrative examples, code snippets, and hands-on exercises, this manual empowers readers to excel, make informed decisions, and derive optimal value from time series data. What you will learn ● Understand the fundamentals of time series data, including temporal patterns, trends, and seasonality. ● Proficiently utilize Python libraries such as pandas, NumPy, and matplotlib for efficient data manipulation and visualization. ● Conduct exploratory analysis of time series data, including identifying patterns, detecting anomalies, and extracting meaningful features. ● Build accurate and reliable predictive models using a variety of machine learning and deep learning techniques, including ARIMA, LSTM, and CNN. ● Perform multivariate and multiple time series forecasting, allowing for more comprehensive analysis and prediction across diverse datasets. ● Evaluate model performance using a range of metrics and validation techniques, ensuring the reliability and robustness of predictive models. Table of Contents 1. Introduction to Time Series 2. Overview of Time Series Libraries in Python 3. Visualization of Time Series Data 4. Exploratory Analysis of Time Series Data 5. Feature Engineering on Time Series 6. Time Series Forecasting – ML Approach Part 1 7. Time Series Forecasting – ML Approach Part 2 8. Time Series Forecasting - DL Approach 9. Multivariate Time Series, Metrics, and Validation Index

Author: Oswaal Editorial Board
Publisher: Oswaal Books
ISBN: 9359581453
Category : Study Aids
Languages : en
Pages : 89

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Book Description
Description of the product: • Strictly as per the Latest Exam Pattern issued by NTA • 100% Updated with 2023 Exam Paper • Previous Years’ Questions (2021-2023) for better Exam insights • Revision Notes for Crisp Revision with Smart Mind Maps • Concept Videos for complex concepts clarity • 800+Questions for Extensive Practice

Author: Charles Bell
Publisher: Springer Nature
ISBN: 1484298616
Category :
Languages : en
Pages : 578

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Book Description

Author: Steven F. Lott
Publisher: Packt Publishing Ltd
ISBN: 1801075239
Category : Computers
Languages : en
Pages : 715

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Book Description
A comprehensive guide to exploring modern Python through data structures, design patterns, and effective object-oriented techniques Key Features Build an intuitive understanding of object-oriented design, from introductory to mature programs Learn the ins and outs of Python syntax, libraries, and best practices Examine a machine-learning case study at the end of each chapter Book Description Object-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Python Object-Oriented Programming, Fourth Edition dives deep into the various aspects of OOP, Python as an OOP language, common and advanced design patterns, and hands-on data manipulation and testing of more complex OOP systems. These concepts are consolidated by open-ended exercises, as well as a real-world case study at the end of every chapter, newly written for this edition. All example code is now compatible with Python 3.9+ syntax and has been updated with type hints for ease of learning. Steven and Dusty provide a comprehensive, illustrative tour of important OOP concepts, such as inheritance, composition, and polymorphism, and explain how they work together with Python's classes and data structures to facilitate good design. In addition, the book also features an in-depth look at Python's exception handling and how functional programming intersects with OOP. Two very powerful automated testing systems, unittest and pytest, are introduced. The final chapter provides a detailed discussion of Python's concurrent programming ecosystem. By the end of the book, you will have a thorough understanding of how to think about and apply object-oriented principles using Python syntax and be able to confidently create robust and reliable programs. What you will learn Implement objects in Python by creating classes and defining methods Extend class functionality using inheritance Use exceptions to handle unusual situations cleanly Understand when to use object-oriented features, and more importantly, when not to use them Discover several widely used design patterns and how they are implemented in Python Uncover the simplicity of unit and integration testing and understand why they are so important Learn to statically type check your dynamic code Understand concurrency with asyncio and how it speeds up programs Who this book is for If you are new to object-oriented programming techniques, or if you have basic Python skills and wish to learn how and when to correctly apply OOP principles in Python, this is the book for you. Moreover, if you are an object-oriented programmer coming from other languages or seeking a leg up in the new world of Python, you will find this book a useful introduction to Python. Minimal previous experience with Python is necessary.

Author: MrExcel's Holy Macro! Books
Publisher: Packt Publishing Ltd
ISBN: 1836647662
Category : Computers
Languages : en
Pages : 343

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Book Description
Master the latest Excel features and elevate your productivity with practical tips and expert guidance. Perfect for all skill levels, this comprehensive guide covers everything from basic tricks to advanced techniques. Key Features Comprehensive coverage of Excel's new 2024 features Practical examples and step-by-step instructions Advanced tips for automation and data visualization Book DescriptionUnlock Excel 2024's potential with this essential guide, featuring 150 advanced techniques designed to elevate your skills. Whether you're automating tasks, creating dynamic dashboards, or utilizing Excel's new AI tools, this guide provides clear, practical instructions. Each chapter is crafted to help you navigate Excel's latest features, from data manipulation to complex formulas and Python integration. This guide offers a hands-on approach, with real-world examples that demonstrate how to apply Excel’s capabilities in practical scenarios. You'll learn to optimize your workflow, enhance data visualization, and make informed decisions based on your analysis. The guide is perfect for intermediate to advanced users looking to stay ahead of the curve and maximize their productivity. By focusing on both the "how" and the "why" of each feature, this guide ensures you not only understand the technical steps but also grasp the underlying principles that make these tools powerful. Whether you're a data analyst, financial professional, or business manager, this guide equips you with the skills to transform your Excel experience, making your work more efficient, accurate, and insightful.What you will learn Master Excel's latest features efficiently Implement advanced data analysis Use dynamic arrays and LAMBDA functions Create interactive dashboards Utilize Python within Excel Automate tasks using Power Query Who this book is for This book is ideal for Excel users of all levels, from beginners to advanced. No prior experience with the latest Excel version is needed, but basic familiarity with Excel is recommended. This course is suitable for professionals in data analysis, finance, administration, and students.