Android Flash. Zaawansowane programowanie aplikacji mobilnych

Stephen Chin, Dean Iverson, Oswald Campesato, Paul Trani

Wejdź w świat tworzenia oprogramowania dla urządzeń mobilnych! Platforma Android z każdym dniem zdobywa tysiące kolejnych użytkowników. Andy Rubin - odpowiedzialny za nią w Google - pochwalił się aktywacją 700 tysięcy nowych urządzeń z tym systemem każdego dnia. Robi wrażenie? Pomyśl, jak wykorzystać ten rynek i stworzyć aplikację, która podbije serca użytkowników. Dzięki możliwości wykorzystania technologii Flash teraz jest to jeszcze łatwiejsze! "Android Flash. Zaawansowane programowanie aplikacji mobilnych" to kompletny przewodnik po budowaniu skomplikowanych, zajmujących aplikacji dla Androida. Dzięki tej książce nauczysz się programować smartfony Android oraz tablety z wykorzystaniem najpopularniejszych frameworków służących do tworzenia bogatych aplikacji internetowych (RIA) dla Androida - Flash i Flex. Gdy wraz z autorami przejrzysz już zestaw narzędzi programistycznych Flasha, dowiesz się, jak dodawać multimedia, animacje i efekty specjalne do aplikacji. Zrozumiesz, jak działa optymalizowanie dla różnorodnych wyświetlaczy oraz jak wykorzystać dane wejściowe pochodzące z aparatu, GPS, mikrofonu i akcelerometru. Poznasz metody tworzenia certyfikatów podpisywania kodu oraz uzyskiwania jak najlepszej wydajności aplikacji. Zapoznasz się z dużą ilością praktycznego, dobrze skomentowanego kodu i zbudujesz trzy kompletne projekty: program do rysowania, odtwarzacz muzyczny Flash oraz aplikację AIR przechowującą informacje o stanach witryn w bazie danych SQLite. Sprawdź możliwości technologii Flash dla platformy Android. Korzystaj z usług geolokalizacyjnych Sprawdź położenie telefonu za pomocą wbudowanych sensorów Wykorzystaj narzędzia przeznaczone dla technologii Flash Opublikuj aplikację w Android Market! Twórz atrakcyjne aplikacje mobilne za pomocą Flasha, Fleksa i Androida!

Angular and Deep Learning Pocket Primer. A Comprehensive Guide to AI and Expert Systems for Professionals

Mercury Learning and Information, Oswald Campesato

As part of the Pocket Primer series, this book introduces basic deep learning concepts and integrates them into Angular 10 applications. It offers a fast-paced introduction to deep learning features and popular classifiers. Covering Angular 10 functionality, deep learning concepts, and key classification algorithms, the book includes code samples and figures. Topics such as TensorFlow and Keras are also explored.The book begins with an introduction to AI and its applications, followed by state space search and heuristic search strategies. You will delve into expert systems, their development life cycle, knowledge acquisition, and representation. These topics lead to a deeper understanding of neural networks, the learning process, and fuzzy logic systems, ensuring a comprehensive grasp of AI and deep learning principles.Understanding these concepts is essential for developing sophisticated AI applications and enhancing Angular 10 projects. This book transitions you from a novice to a proficient developer, equipped with practical skills and knowledge. Advanced topics like fuzzy expert systems and logic programming are covered, culminating in advanced Prolog. Companion files with source code and color figures enhance the learning experience, making this book an invaluable resource for integrating deep learning with Angular 10.

Angular and Machine Learning Pocket Primer. A Comprehensive Guide to Angular and Integrating Machine Learning

Mercury Learning and Information, Oswald Campesato

As part of the best-selling *Pocket Primer* series, this book introduces readers to basic machine learning concepts and integrates them into Angular applications. It offers a fast-paced introduction to essential machine learning features and an overview of popular classifiers. Covering Angular functionality, basic machine learning concepts, and key classification algorithms, the book includes numerous code samples and figures. Topics such as TensorFlow and Keras are also explored.The book begins with a quick introduction to Angular, followed by UI controls, user input, and forms and services. As you progress, you will delve into machine learning, working with classifiers, and integrating TensorFlow.js with Angular. These foundational topics ensure a comprehensive grasp of both Angular and machine learning principles, equipping you with practical skills for developing sophisticated applications.Understanding these concepts is crucial for enhancing Angular projects with machine learning capabilities. This book transitions you from a novice to a proficient developer, equipped with the knowledge and tools needed to create advanced applications. Companion files with source code and color figures enhance the learning experience, making this book an invaluable resource for integrating machine learning with Angular.

Artificial Intelligence, Machine Learning, and Deep Learning. A Practical Guide to Advanced AI Techniques

Mercury Learning and Information, Oswald Campesato

This book introduces AI, then explores machine learning, deep learning, natural language processing (NLP), and reinforcement learning. Readers learn about classifiers like logistic regression, k-NN, decision trees, random forests, and SVMs. It delves into deep learning architectures such as CNNs, RNNs, LSTMs, and autoencoders, with Keras-based code samples supplementing the theory.Starting with a foundational AI overview, the course progresses into machine learning, explaining classifiers and their applications. It continues with deep learning, focusing on architectures like CNNs and RNNs. Advanced topics include LSTMs and autoencoders, essential for modern AI. The book also covers NLP and reinforcement learning, emphasizing their importance.Understanding these concepts is vital for developing advanced AI systems. This book transitions you from beginner to proficient AI practitioner, combining theoretical knowledge and practical skills. Appendices on Keras, TensorFlow 2, and Pandas enrich the learning experience. By the end, readers will understand AI principles and be ready to apply them in real-world scenarios.

Bash Command Line and Shell Scripts Pocket Primer. Mastering Bash Commands and Scripting Techniques

Mercury Learning and Information, Oswald Campesato

As part of the best-selling Pocket Primer series, this book introduces readers to useful command-line utilities for creating powerful shell scripts. It focuses on the “bash” command set, though many concepts apply to other command shells like sh, ksh, zsh, and csh. The book covers piping data between commands and using versatile sed and awk commands. Aimed at beginners, it also serves as a good reference for those with some experience in shell scripting.The journey starts with an introduction to bash, covering files and directories, useful commands, and conditional logic with loops. Readers then learn to filter data with grep, transform data with sed, and work with awk. The book introduces shell scripts, showcasing their use with grep and awk for data manipulation. Various scripts are provided for data scientists and analysts needing shell-based solutions for text file cleaning.Understanding these concepts is crucial for simplifying routine tasks and creating efficient shell scripts. This book transitions readers from novices to proficient scriptwriters, combining theoretical knowledge and practical skills. Companion files with source code examples enhance learning. By the end, readers will be equipped to implement shell scripts in real-world scenarios.

Bash for Data Scientists. A Comprehensive Guide to Shell Scripting for Data Science Tasks

Mercury Learning and Information, Oswald Campesato

This book introduces powerful command line utilities for creating efficient shell scripts to process datasets. Using the bash shell, the examples and scripts focus on small datasets to help readers understand the features of grep, sed, and awk. Companion files with code are available for download from the publisher.The course starts with an introduction to the basics, covering files and directories, and useful commands. It then progresses to conditional logic and loops, providing a solid foundation for processing datasets. Detailed chapters on using grep, sed, and awk illustrate their capabilities in handling and cleaning various types of datasets effectively.Advanced topics include processing datasets with Pandas, exploring NoSQL, SQLite, and Python. The book equips data scientists, analysts, and anyone seeking shell-based solutions with practical skills. By the end, users will be adept at creating robust scripts for dataset processing, combining command line utilities for optimal results.

C Programming Pocket Primer. An Essential Guide to C Programming Basics

Mercury Learning and Information, Oswald Campesato

As part of the Pocket Primer series, this book provides an overview of major concepts in C programming. It covers essential techniques, including up-to-date information on the C11 standard and comprehensive chapters on pointers. Companion files with source code and figures from the book are included.The course begins with an introduction to C, moving through conditional logic, loops, and arrays. It then delves into functions and provides detailed coverage of pointers, essential for mastering C programming. Miscellaneous topics are also addressed to ensure a well-rounded understanding.Understanding these concepts is crucial for developing efficient C programs. This book transitions readers from beginners to proficient C programmers, combining theoretical knowledge with practical skills. Companion files enhance the learning experience, making this book an invaluable resource for mastering C programming.

CSS3 and SVG with Claude 3. Mastering CSS3 and SVG: Techniques for Advanced Data Visualization and Animation

Mercury Learning and Information, Oswald Campesato

This book is an essential guide for mastering advanced CSS3 and SVG techniques, ideal for web developers aiming to create visually striking and interactive web content. It starts with an in-depth look at CSS3, covering shadow effects, gradients, 2D and 3D transforms, and sophisticated animations. You'll learn to implement complex styling, use media queries for responsive design, and create dynamic keyframe animations. Security practices and effective use of CSS3 are also addressed.Moving to SVG, the book explores creating scalable vector graphics for advanced data visualizations and animations. You'll learn to use SVG elements like shapes, gradients, and Bezier curves, and how to seamlessly integrate them with CSS3 for dynamic, interactive graphics. Detailed tutorials on SVG filters, transforms, and animations enable you to build intricate visual effects and engaging content. Practical examples show how to combine CSS3 and SVG for responsive, high-performance web projects.By the end, you’ll have the skills to craft compelling web applications using CSS3 and SVG, whether you're a beginner or an experienced developer looking to elevate your web design expertise.

Data Literacy With Python. A Comprehensive Guide to Understanding and Analyzing Data with Python

Mercury Learning and Information, Oswald Campesato

This book ushers readers into the world of data, emphasizing its importance in modern industries and how its management leads to insightful decision-making. Using Python 3, the book introduces foundational data tasks and progresses to advanced model training concepts. Detailed, step-by-step Python examples help readers master training models, starting with the kNN algorithm and moving to other classifiers with minimal code adjustments. Tools like Sweetviz, Skimpy, Matplotlib, and Seaborn are introduced for hands-on chart and graph rendering.The course begins with working with data, detecting outliers and anomalies, and cleaning datasets. It then introduces statistics and progresses to using Matplotlib and Seaborn for data visualization. Each chapter builds on the previous one, ensuring a comprehensive understanding of data management and analysis.These concepts are crucial for making data-driven decisions. This book transitions readers from basic data handling to advanced model training, blending theoretical knowledge with practical skills. Companion files with source code and data sets enhance the learning experience, making this book an invaluable resource for mastering data science with Python.

Data Science Fundamentals Pocket Primer. An Essential Guide to Data Science Concepts and Techniques

Mercury Learning and Information, Oswald Campesato

This book, part of the Pocket Primer series, introduces the basic concepts of data science using Python 3 and other applications. It offers a fast-paced introduction to data analytics, statistics, data visualization, linear algebra, and regular expressions. The book features numerous code samples using Python, NumPy, R, SQL, NoSQL, and Pandas. Companion files with source code and color figures are available.Understanding data science is crucial in today's data-driven world. This book provides a comprehensive introduction, covering key areas such as Python 3, data visualization, and statistical concepts. The practical code samples and hands-on approach make it ideal for beginners and those looking to enhance their skills.The journey begins with working with data, followed by an introduction to probability, statistics, and linear algebra. It then delves into Python, NumPy, Pandas, R, regular expressions, and SQL/NoSQL, concluding with data visualization techniques. This structured approach ensures a solid foundation in data science.

Data Wrangling Using Pandas, SQL, and Java. A Comprehensive Guide to Data Cleaning and Transformation

Mercury Learning and Information, Oswald Campesato

This book is designed for aspiring data scientists and those involved in data cleaning. It covers features of NumPy and Pandas, along with creating databases and tables in MySQL. It also addresses various data wrangling tasks using Python scripts and awk-based shell scripts. Companion files with code are available from the publisher.Understanding data cleaning and manipulation is vital for data scientists. This book provides a comprehensive introduction to essential tools and techniques. From Python basics to advanced data wrangling, it equips readers with the skills needed to manage and clean data effectively.The journey begins with an introduction to Python and progresses through working with data, Pandas, and SQL. It also covers Java, JSON, XML, and specific data cleaning tasks. The book culminates with detailed data wrangling techniques, ensuring readers gain practical, hands-on experience in data management.

Dealing With Data Pocket Primer. A Comprehensive Guide to Data Handling Techniques

Mercury Learning and Information, Oswald Campesato

This book introduces the basic concepts of managing data using various computer languages and applications. It is designed as a fast-paced introduction to key features of data management, including statistical concepts, data-related techniques, Pandas, RDBMS, SQL, NLP topics, Matplotlib, and data visualization. The companion files with source code and color figures enhance the learning experience.Understanding these concepts is crucial for anyone looking to manage data effectively. The book covers the fundamentals of probability and statistics, working with data using Pandas, managing databases with SQL and MySQL, and cleaning data using NLP techniques. It also delves into data visualization, providing practical insights and numerous code samples.The journey begins with an introduction to probability and statistics, moving on to working with data and Pandas. It then covers RDBMS and SQL, focusing on practical SQL and MySQL usage. The book concludes with NLP, data cleaning, and visualization techniques, equipping readers with a comprehensive understanding of data management.

Google Gemini for Python. Coding with Bard: Mastering Python with Google's AI Tools

Mercury Learning and Information, Oswald Campesato

This book bridges Python 3 programming and Generative AI, equipping readers with the skills to navigate both domains confidently. It starts with Python basics, covering data types, number formatting, text manipulation, loops, functions, data structures, NumPy, Pandas, conditional logic, and reserved words. You'll also learn about handling user input, managing exceptions, and working with command-line arguments.The journey continues into Generative AI, distinguishing it from Conversational AI. It introduces popular platforms and models, including Bard (now called Gemini) and its competitors, providing insights into their capabilities, strengths, weaknesses, and applications. The final chapters show how to generate various Python 3 code samples using Gemini.Understanding these concepts is crucial for modern programming and AI applications. This book transitions readers from basic Python programming to advanced AI techniques, blending theoretical knowledge with practical skills. Companion files with source code and figures enhance the learning experience, making this an essential resource for mastering Python 3 and Generative AI.

Java for Developers Pocket Primer. A Concise Guide to Mastering Java Programming

Mercury Learning and Information, Oswald Campesato

As part of the best-selling Pocket Primer series, this book offers a thorough introduction to Java development for beginners. It provides a fast-paced overview of core Java concepts and APIs, using Java 8 code samples. Companion files with source code are included.The journey begins with an introduction to Java, covering Boolean logic, Unicode, and user input. It progresses through methods, constructors, loops, arrays, and recursion. The course then delves into object-oriented programming (OOP) concepts and data structures. Advanced topics include streams, file handling, and integrating Java with SQL. The book also lists new features from Java 9 to Java 13.Understanding these concepts is crucial for developing efficient Java applications. This book transitions readers from basic to advanced Java programming, blending theoretical knowledge with practical skills. Companion files enhance the learning experience, making this book an essential resource for mastering Java development.

Large Language Models An Introduction. Understanding the Fundamentals and Applications of Generative AI

Mercury Learning and Information, Oswald Campesato

This book provides a comprehensive overview of large language models (LLMs) and generative AI, covering foundational principles, advanced concepts, and practical applications. It begins with an introduction to the generative AI landscape, examining key features, popular techniques, and its influence on industries like art, business, and technology. The book also explores prominent models like ChatGPT and GPT-4, detailing their architectures, capabilities, and applications in text generation, code assistance, and conversational AI.Additionally, the book traces the evolution of LLMs, particularly focusing on the BERT family and its wide-ranging applications in natural language processing, translation, and multilingual tasks. Readers will also gain expertise in prompt engineering, learning practical tips and examples to interact more effectively with LLMs.In later chapters, the book tackles advanced topics such as fine-tuning LLMs, working with SVG, and concepts like few-shot learning and reinforcement learning. It concludes with discussions on ethical issues, biases in generative AI, and emerging trends like AI’s integration with IoT, quantum computing, and neuromorphic computing. This guide equips professionals and enthusiasts with a thorough understanding of generative AI's present and future.

Natural Language Processing and Machine Learning for Developers. A Practical Guide to Advanced Techniques and Applications of NLP

Mercury Learning and Information, Oswald Campesato

This book introduces developers to basic concepts in NLP and machine learning, providing numerous code samples to support the topics covered. The journey begins with introductory material on NumPy and Pandas, essential for data manipulation. Following this, chapters delve into NLP concepts, algorithms, and toolkits, providing a solid foundation in natural language processing.As you progress, the book covers machine learning fundamentals and classifiers, demonstrating how these techniques are applied in NLP. Practical examples using TF2 and Keras illustrate how to implement various NLP tasks. Advanced topics include the Transformer architecture, BERT-based models, and the GPT family of models, showcasing the latest advancements in the field.The final chapters and appendices offer a comprehensive overview of related topics, including data and statistics, Python3, regular expressions, and data visualization with Matplotlib and Seaborn. Companion files with source code and figures ensure a hands-on learning experience. This book equips you with the knowledge and tools needed to excel in NLP and machine learning.

Natural Language Processing Fundamentals for Developers. A Practical Guide to Building NLP Applications

Mercury Learning and Information, Oswald Campesato

This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to those with varied technical backgrounds, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.

Natural Language Processing using R Pocket Primer. Learn Essential NLP Techniques and Tools for Developers

Mercury Learning and Information, Oswald Campesato

This book is for developers seeking an overview of basic concepts in Natural Language Processing (NLP). It caters to a technical audience, offering numerous code samples and listings to illustrate the wide range of topics covered. The journey begins with managing data relevant to NLP, followed by two chapters on fundamental NLP concepts. This foundation is reinforced with Python code samples that bring these concepts to life.The book then delves into practical NLP applications, such as sentiment analysis, recommender systems, COVID-19 analysis, spam detection, and chatbots. These examples provide real-world context and demonstrate how NLP techniques can be applied to solve common problems. The final chapter introduces advanced topics, including the Transformer architecture, BERT-based models, and the GPT family, highlighting the latest state-of-the-art developments in the field.Appendices offer additional resources, including Python code samples on regular expressions and probability/statistical concepts, ensuring a well-rounded understanding. Companion files with source code and figures enhance the learning experience, making this book a comprehensive guide for mastering NLP techniques and applications.

Pandas Basics. Mastering Data Analysis with Pandas

Mercury Learning and Information, Oswald Campesato

This book is essential for aspiring data scientists and anyone needing to perform data cleaning using Pandas and NumPy. It offers numerous code samples and comprehensive coverage of NumPy and Pandas features, including writing regular expressions. Chapter 3 introduces fundamental statistical concepts, while Chapter 7 delves into data visualization using Matplotlib and Seaborn. Companion files with code are available for download from the publisher.Starting with an introduction to Python, the course progresses through working with data, and then moves into Pandas, covering its functionalities in three detailed chapters. The statistical concepts provided are crucial for analyzing data effectively, while the visualization techniques enhance the ability to present data insights clearly.By the end of this course, users will have a solid foundation in data manipulation and cleaning, statistical analysis, and data visualization, enabling them to tackle real-world data science tasks confidently and efficiently.

Python 3 and Data Analytics Pocket Primer. A Quick Guide to NumPy, Pandas, and Data Visualization

Mercury Learning and Information, Oswald Campesato

This book, part of the best-selling Pocket Primer series, introduces readers to the fundamental concepts of data analytics using Python 3. The course begins with a concise introduction to Python, covering essential programming constructs and data manipulation techniques. This foundation sets the stage for deeper dives into data analytics, emphasizing the importance of data cleaning, a critical step in any data analysis process.Following the Python basics, the course explores powerful libraries such as NumPy and Pandas for efficient data handling and manipulation. It then delves into statistical concepts, providing the necessary background for understanding data distributions and analytical methods. The course culminates in data visualization techniques using Matplotlib and Seaborn, demonstrating how to effectively communicate insights through graphical representations.Throughout the course, numerous code samples and practical examples are provided, reinforcing learning and offering hands-on experience. Companion files with source code and figures are available online, supporting the learning journey. This comprehensive guide equips both beginners and seasoned professionals with the skills needed to excel in data analytics.

Python 3 and Data Visualization. Mastering Graphics and Data Manipulation with Python

Mercury Learning and Information, Oswald Campesato

Python 3 and Data Visualization provides an in-depth exploration of Python 3 programming and data visualization techniques. The course begins with an introduction to Python, covering essential topics from basic data types and loops to advanced constructs such as dictionaries and matrices. This foundation prepares readers for the next section, which focuses on NumPy and its powerful array operations, seamlessly leading into data visualization using prominent libraries like Matplotlib.Chapter 6 delves into Seaborn's rich visualization tools, providing insights into datasets like Iris and Titanic. The appendix covers additional visualization tools and techniques, including SVG graphics and D3 for dynamic visualizations. The companion files include numerous Python code samples and figures, enhancing the learning experience.From foundational Python concepts to advanced data visualization techniques, this course serves as a comprehensive resource for both beginners and seasoned professionals, equipping them with the necessary skills to effectively visualize data.

Python 3 and Machine Learning Using ChatGPT / GPT-4. Harness the Power of Python, Machine Learning, and Generative AI

Mercury Learning and Information, Oswald Campesato

This book bridges the gap between theoretical knowledge and practical application in Python programming, machine learning, and using ChatGPT-4 in data science. It starts with an introduction to Pandas for data manipulation and analysis. The book then explores various machine learning classifiers, from kNN to SVMs. Later chapters cover GPT-4's capabilities, enhancing linear regression analysis, and using ChatGPT in data visualization, including AI apps, GANs, and DALL-E.The journey begins with mastering Pandas and machine learning fundamentals. It progresses to applying GPT-4 in linear regression and machine learning classifiers. The final chapters focus on using ChatGPT for data visualization, making complex results accessible and understandable.Understanding these concepts is crucial for modern data scientists. This book transitions readers from basic Python programming to advanced applications of ChatGPT-4 in data science. Companion files with source code, datasets, and figures enhance learning, making this an essential resource for mastering Python, machine learning, and AI-driven data visualization.

Python 3 Data Visualization Using ChatGPT / GPT-4. Master Python Visualization Techniques with AI Integration

Mercury Learning and Information, Oswald Campesato

This book teaches Python 3 programming and data visualization, exploring cutting-edge techniques with ChatGPT/GPT-4 for generating compelling visuals. It starts with Python essentials, covering basic data types, loops, functions, and advanced constructs like dictionaries and matrices. The journey progresses to NumPy's array operations and data visualization using libraries such as Matplotlib and Seaborn. The book also covers tools like SVG graphics and D3 for dynamic visualizations.The course begins with foundational Python concepts, moves into NumPy and data visualization with Pandas, Matplotlib, and Seaborn. Advanced chapters explore ChatGPT and GPT-4, demonstrating their use in creating data visualizations from datasets like the Titanic. Each chapter builds on the previous one, ensuring a comprehensive understanding of Python and visualization techniques.These concepts are crucial for Python practitioners, data scientists, and anyone in data analytics. This book transitions readers from basic Python programming to advanced data visualization, blending theoretical knowledge with practical skills. Companion files with code, datasets, and figures enhance learning, making this an essential resource for mastering Python and data visualization.

Python 3 Data Visualization Using Google Gemini. Unlock the Power of Python and Google Gemini for Stunning Data Visualizations

Mercury Learning and Information, Oswald Campesato

This book teaches Python 3 programming and data visualization, exploring cutting-edge techniques with ChatGPT/GPT-4 for generating compelling visuals. It starts with Python essentials, covering basic data types, loops, functions, and advanced constructs like dictionaries and matrices. The journey progresses to NumPy's array operations and data visualization using libraries such as Matplotlib and Seaborn. The book also covers tools like SVG graphics and D3 for dynamic visualizations.The course begins with foundational Python concepts, moves into NumPy and data visualization with Pandas, Matplotlib, and Seaborn. Advanced chapters explore ChatGPT and GPT-4, demonstrating their use in creating data visualizations from datasets like the Titanic. Each chapter builds on the previous one, ensuring a comprehensive understanding of Python and visualization techniques.These concepts are crucial for Python practitioners, data scientists, and anyone in data analytics. This book transitions readers from basic Python programming to advanced data visualization, blending theoretical knowledge with practical skills. Companion files with code, datasets, and figures enhance learning, making this an essential resource for mastering Python and data visualization.