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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.
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, Armando Fandango, 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
Python. An Introduction to Python Programming
Mercury Learning and Information, James R. Parker
This book introduces programming concepts using Python 3, designed for beginners and hobbyists with no prior programming experience. It covers loops, strings, functions, files, graphics, multimedia, algorithms, classes, and more. Many examples are based on video game development, making learning engaging and practical. The book uses a just-in-time presentation style, providing material when it's needed, and includes companion files with source code, exercises, projects, and figures.The course starts with an overview of modern computers and basic programming concepts. It progresses through topics like repetition, sequences, functions, file input/output, classes, graphics, data manipulation, and multimedia. The latter chapters focus on basic algorithms, programming for the sciences, writing good programs, parsing, and communicating using graphics and Pygame.By the end of the course, students will have a solid understanding of programming fundamentals, enhanced by practical applications in video game development. This approach not only makes learning enjoyable but also equips students with the skills needed for further studies in computer science and programming.
Cuantum Technologies LLC
Embark on a transformative journey with this course designed to equip you with robust Python and SQL skills. Starting with an introduction to Python, you'll delve into fundamental building blocks, control flow, functions, and object-oriented programming. As you progress, you'll master data structures, file I/O, exception handling, and the Python Standard Library, ensuring a solid foundation in Python.The course then transitions to SQL, beginning with an introduction and covering basics, and proceeding to advanced querying techniques. You'll learn about database administration and how Python integrates seamlessly with SQL, enhancing your data manipulation capabilities. By combining Python with SQLAlchemy, you'll perform advanced database operations and execute complex data analysis tasks, preparing you for real-world challenges.By the end of this course, you will have developed the expertise to utilize Python and SQL for scientific computing, data analysis, and database management. This comprehensive learning path ensures you can tackle diverse projects, from basic scripting to sophisticated data operations, making you a valuable asset in the tech industry. You'll also gain hands-on experience with real-world datasets, enhancing your problem-solving skills and boosting your confidence.
Dr. Joshua Eckroth
Artificial Intelligence (AI) is the newest technology that’s being employed among varied businesses, industries, and sectors. Python Artificial Intelligence Projects for Beginners demonstrates AI projects in Python, covering modern techniques that make up the world of Artificial Intelligence.This book begins with helping you to build your first prediction model using the popular Python library, scikit-learn. You will understand how to build a classifier using an effective machine learning technique, random forest, and decision trees. With exciting projects on predicting bird species, analyzing student performance data, song genre identification, and spam detection, you will learn the fundamentals and various algorithms and techniques that foster the development of these smart applications. In the concluding chapters, you will also understand deep learning and neural network mechanisms through these projects with the help of the Keras library.By the end of this book, you will be confident in building your own AI projects with Python and be ready to take on more advanced projects as you progress