Ebooks
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.
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.
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.
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 for Machine Learning. Harness the Power of Python for Advanced Machine Learning Projects
Mercury Learning and Information, Oswald Campesato
This book introduces basic Python 3 programming concepts related to machine learning. The first four chapters provide a fast-paced introduction to Python 3, NumPy, and Pandas. The fifth chapter covers fundamental machine learning concepts. The sixth chapter dives into machine learning classifiers, such as logistic regression, k-NN, decision trees, random forests, and SVMs. The final chapter includes material on natural language processing (NLP) and reinforcement learning (RL). Keras-based code samples supplement the theoretical discussion.The course begins with Python basics, including conditional logic, loops, functions, and collections. It then explores data manipulation with NumPy and Pandas. The journey continues with an introduction to machine learning, focusing on essential concepts and classifiers. Advanced topics like NLP and RL are covered, ensuring a comprehensive understanding of machine learning.These concepts are crucial for developing machine learning applications. This book transitions readers from basic Python programming to advanced machine learning techniques, blending theory with practical skills. Appendices for regular expressions, Keras, and TensorFlow 2, along with companion files, enhance learning, making this an essential resource for mastering Python and machine learning.
Python 3. Kolejne lekcje dla nowych programistów
Zed A. Shaw
Jeśli masz już za sobą napisanie pierwszych programów w Pythonie, to już wiesz, jak bardzo wszechstronny jest ten język i że jego możliwości są imponujące. Python nadaje się do bardzo wielu zastosowań, jednak jeśli chcesz go wykorzystać w pełni, musisz wyjść poza podstawy. Efektywny programista korzysta z wiedzy wykraczającej poza znajomość struktur języka, poza tym jest zdolny do obiektywnej refleksji nad własnymi możliwościami i stara się cały czas doskonalić swój warsztat. Dzięki tej książce, zanim się spostrzeżesz, wykonasz 52 interesujące i świetnie przygotowane projekty, dzięki którym zyskasz kluczowe praktyczne umiejętności i pogłębisz rozumienie sedna pracy programisty. Odkryjesz sposoby analizy problemu i nauczysz się projektować sposób jego implementacji w programie. Później zaczniesz projektować konkretne rozwiązania, dbając o ich prostotę i elegancję. Wystarczy, że wykażesz się dyscypliną, zaangażowaniem i wytrwałością, a już wkrótce zrozumiesz znaczenie procesu, rozwiniesz kreatywność, a przede wszystkim zadbasz o jakość tworzonego kodu. Twoim celem nie będzie już tylko pisanie "kodu, który działa". Zaczniesz tworzyć znakomity kod i staniesz się prawdziwym programistą, biegłym w Pythonie. W tej książce: praca ze złożonymi projektami korzystanie ze struktur danych algorytmy i przetwarzanie struktur danych techniki parsowania i przetwarzania tekstu modelowanie danych za pomocą języka SQL stosowanie prostych i zaawansowanych narzędzi systemu Unix Proces. Kreatywność. Jakość. Python.
Python 3 Object Oriented Programming. Harness the power of Python 3 objects
Dusty Phillips
Object Oriented Programming is a very important aspect of modern programming languages. The basic principles of Object Oriented Programming are relatively easy to learn. Putting them together into working designs can be challenging.This book makes programming more of a pleasure than a chore using powerful Python 3 object-oriented features of Python 3. It clearly demonstrates the core OOP principles and how to correctly implement OOP in Python. Object Oriented Programming ranks high in importance among the many models Python supports. Yet, many programmers never bother learning the powerful features that make this language object oriented.The book teaches when and how OOP should be correctly applied. It emphasizes not only the simple syntax of OOP in Python, but also how to combine these objects into well-designed software.This book will introduce you to the terminology of the object-oriented paradigm, focusing on object-oriented design with step-by-step examples. It will take you from simple inheritance, one of the most useful tools in the object-oriented programmer's toolbox, all the way through to cooperative inheritance, one of the most complicated. You will be able to raise, handle, define, and manipulate exceptions.You will be able to integrate the object-oriented and the not-so-object-oriented aspects of Python. You will also be able to create maintainable applications by studying higher level design patterns. You'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced to you. You'll understand the joy of unit testing and just how easy they are to create. You'll even study higher level libraries such as database connectors and GUI toolkits and how they apply object-oriented principles.
Dusty Phillips
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. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software.Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem.By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.
Dusty Phillips
Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax.Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception.Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software.You'll get an in-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style. This book will not just teach Python syntax, but will also build your confidence in how to program.You will also learn how to create maintainable applications by studying higher level design patterns. Following this, you'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced in the book. After you discover the joy of unit testing and just how easy it can be, you'll study higher level libraries such as database connectors and GUI toolkits and learn how they uniquely apply object-oriented principles. You'll learn how these principles will allow you to make greater use of key members of the Python eco-system such as Django and Kivy.This new edition includes all the topics that made Python 3 Object-oriented Programming an instant Packt classic. It's also packed with updated content to reflect recent changes in the core Python library and covers modern third-party packages that were not available on the Python 3 platform when the book was first published.
Python 3. Projekty dla początkujących i pasjonatów
Adam Jurkiewicz
Twórz różne programy w Pythonie - i baw się świetnie! Jeśli: chcesz poznać język Python od strony praktycznej przymierzasz się do matury z informatyki marzysz o karierze programisty to doskonale trafiłeś! Dzięki tej książce przekonasz się, jak wspaniałą przygodą jest programowanie i jak łatwo ją zacząć! Poznasz podstawy Pythona, dowiesz się, jak pisać i formatować kod, a także szybko nauczysz się uruchamiać swoje programy. Instrukcje sterujące, operatory, typy danych, funkcje, klasy i moduły nie będą miały przed Tobą tajemnic, a to jeszcze nie koniec! Przede wszystkim będziesz poznawać Pythona od strony praktycznej, tworząc projekty prawdziwych gier i symulacji oraz aplikacje do wizualizacji danych i anonimizowania metadanych plików graficznych. Możesz użyć tej książki jako pomocy w przygotowaniu do matury i wsparcia w wyborze drogi zawodowej. Przekonaj się, że nauka może być najlepszą zabawą. Baw się dobrze i zdaj egzamin celująco - oczywiście z Pythonem! środowisko IDLE podstawy Pythona w wersji 3.6 i wyższej konstrukcje języka projekty gier symulacje fizyczne prezentacja i wizualizacja danych praktyczne zastosowania Pythona Okiełznaj Pythona i naucz się programować!
Python 3. Proste wprowadzenie do fascynującego świata programowania
Zed A. Shaw
Python jest dojrzałym, elastycznym i bardzo wszechstronnym językiem programowania. Nadaje się do budowy przeróżnych aplikacji, a także do tworzenia programów służących do bardzo specyficznych zastosowań, takich jak badania naukowe. Aby jednak w pełni wykorzystać te imponujące możliwości, musisz pisać dobry kod: przejrzysty, zwięzły, działający poprawnie. Niestety, nie jest łatwo nauczyć się dobrego programowania. To coś więcej niż przyswojenie zestawu poleceń i słów kluczowych. Wymaga czasu, wysiłku, sporego zaangażowania i... dobrego przewodnika na tej trudnej ścieżce. Niniejsza książka jest właśnie takim dobrym przewodnikiem dla początkujących programistów. Jest napisana w sposób łatwy i wciągający. Duży nacisk położono na analizę tworzonego kodu. Jeśli tylko skoncentrujesz się na wykonywanych zadaniach, zdobędziesz się na zaangażowanie i dokładność, zrozumienie znaczenia każdej linii programu przyjdzie łatwo. Wartościowym elementem książki są wskazówki, jak zepsuć napisany kod, a następnie go zabezpieczyć. Dzięki temu łatwiej Ci przyjdzie unikanie błędów. Dzięki tej książce zdobędziesz trzy najważniejsze umiejętności każdego programisty: czytanie i pisanie ze zrozumieniem, dbałość o szczegóły oraz dostrzeganie różnic. Najistotniejsze zagadnienia poruszone w książce: przygotowanie kompletnego środowiska programistycznego organizowanie, pisanie, psucie i naprawianie kodu programowanie obiektowe projektowanie programu i testowanie kodu podstawy budowy aplikacji internetowych i prostszych gier Zrozum Pythona, pisz dobry kod!
Python 3 Text Processing with NLTK 3 Cookbook. - Second Edition
Jacob Perkins
This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you’ve learned the limits of regular expressions the hard way, or you’ve realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.
Python 3. The Comprehensive Guide
Rheinwerk Publishing, Inc, Johannes Ernesti, Peter Kaiser
This in-depth guide to Python 3 begins by helping readers install the language and understand its core syntax through interactive exploration. Early chapters cover variables, control structures, functions, and data types like lists, tuples, dictionaries, and sets. Readers then move into file handling, error management, and object-oriented programming, building a solid foundation for real-world development.As the journey continues, the book introduces advanced concepts including decorators, generators, type hints, structural pattern matching, and context managers. It thoroughly explores the Python standard library, with practical applications in math, file systems, logging, regular expressions, parallel processing, and debugging. Readers also learn how to manage packages, virtual environments, and distributions.Later chapters shift to applied development—building GUIs with tkinter and PySide6, creating web applications with Django, and working with scientific tools like NumPy, pandas, and SciPy. The book concludes with insights on using alternative interpreters, localization, and migrating from Python 2 to 3. This resource grows with the reader, from basics to expert-level Python programming.
Python 3 Using ChatGPT / GPT-4. Harnessing AI for Efficient Python Programming
Mercury Learning and Information, Oswald Campesato
This book is for people who want to learn Python 3 and how to use ChatGPT with Python. It starts with an introduction to Python programming, covering data types, number formatting, Unicode handling, and text manipulation. The book then covers loops, conditional logic, reserved words, user input, exception management, and command-line arguments.The journey continues into Generative AI, discussing its distinction from Conversational AI. Popular platforms like ChatGPT and GPT-4 are explored, along with their strengths, weaknesses, and potential applications. The book shows how to generate Python 3 code samples via ChatGPT using the “Code Interpreter” plugin.Understanding these concepts is crucial for navigating Python and AI. This book transitions readers from basic Python programming to advanced AI applications, blending theory with practical skills. Companion files with code samples and figures enhance learning, making this an essential resource for mastering Python and ChatGPT.
Giuseppe Bonaccorso, Rajalingappaa Shanmugamani
This Learning Path is your complete guide to quickly getting to grips with popular machine learning algorithms. You'll be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this Learning Path will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries. You'll bring the use of TensorFlow and Keras to build deep learning models, using concepts such as transfer learning, generative adversarial networks, and deep reinforcement learning. Next, you'll learn the advanced features of TensorFlow1.x, such as distributed TensorFlow with TF clusters, deploy production models with TensorFlow Serving. You'll implement different techniques related to object classification, object detection, image segmentation, and more. By the end of this Learning Path, you'll have obtained in-depth knowledge of TensorFlow, making you the go-to person for solving artificial intelligence problemsThis Learning Path includes content from the following Packt products:• Mastering Machine Learning Algorithms by Giuseppe Bonaccorso• Mastering TensorFlow 1.x by Armando Fandango• Deep Learning for Computer Vision by Rajalingappaa Shanmugamani
Ashish Kumar, Joseph Babcock
Social Media and the Internet of Things have resulted in an avalanche of data. Data is powerful but not in its raw form; it needs to be processed and modeled, and Python is one of the most robust tools out there to do so. It has an array of packages for predictive modeling and a suite of IDEs to choose from. Using the Python programming language, analysts can use these sophisticated methods to build scalable analytic applications. This book is your guide to getting started with predictive analytics using Python.You'll balance both statistical and mathematical concepts, and implement them in Python using libraries such as pandas, scikit-learn, and NumPy. Through case studies and code examples using popular open-source Python libraries, this book illustrates the complete development process for analytic applications. Covering a wide range of algorithms for classification, regression, clustering, as well as cutting-edge techniques such as deep learning, this book illustrates explains how these methods work. You will learn to choose the right approach for your problem and how to develop engaging visualizations to bring to life the insights of predictive modeling.Finally, you will learn best practices in predictive modeling, as well as the different applications of predictive modeling in the modern world. The course provides you with highly practical content from the following Packt books:1. Learning Predictive Analytics with Python2. Mastering Predictive Analytics with Python