Python

Odkryj, jak pisać czysty, czytelny i skalowalny kod w Pythonie.Książka „Dobre praktyki i wzorce projektowe w Python” to praktyczny przewodnik po zasadach SOLID, wzorcach projektowych oraz programowaniu obiektowym. Dowiesz się, jak zarządzać konfiguracją i zależnościami, a także jak stosować wzorce kreacyjne, strukturalne i behawioralne, by budować systemy łatwe w utrzymaniu i odporne na zmiany.Każdy temat poparto przykładami w Pythonie, dzięki czemu szybko wdrożysz poznane rozwiązania w praktyce. To książka dla początkujących i doświadczonych programistów, którzy chcą udoskonalić swój kod i zrozumieć, jak projektować nowoczesne aplikacje.

What You’ll Learn●  Python Fundamentals – Variables, loops, functions, and more explained in a fun way.●  Handling User Input – Making interactive programs.●  Decision Making – Writing smart code using if statements.●  Working with Lists and Dictionaries – Storing and managing data.●  File Handling – Reading and writing files.●  Object-Oriented Programming (OOP) – Learning to code like a pro.●  Error Handling – Preventing your programs from crashing.●  APIs & Web Data – Fetching real-time information.●  Databases – Storing and retrieving data efficiently.●  Final Project – Bringing everything together in a real-world Python application.

Master Python with solved exercises and practical projects to learn coding in a clear, progressive, and efficient way.Become a skilled Python developer: learn to create scripts, automate tasks, and develop robust applications.Go from beginner to Python expert with this complete guide: foundational concepts, advanced techniques, and real-world projects.Learn Python 3 with simple explanations, practical examples, and hands-on guidance to turn your ideas into real projects.

Maîtrisez Python avec des exercices corrigés et des projets pratiques pour apprendre à coder de manière claire, progressive et efficace.Devenez développeur Python compétent : apprenez à créer des scripts, automatiser des tâches et développer des applications robustes.Passez de débutant à expert en Python grâce à ce guide complet : concepts de base, techniques avancées et projets concrets.Apprenez Python 3 avec des explications simples, des exemples concrets et une approche pratique pour transformer vos idées en projets réels.

In this book, we've gone through all the ins and outs of Ruby, turning theoretical ideas into real-world skills that let you build solid and fast applications. You've got the hang of writing clean, reusable code using blocks, procs, and lambdas, which really shows off Ruby's expressive syntax. You've also learned to handle complex data transformations effortlessly by diving into enumerators, making your programs powerful and elegant.

This book will help you explore the foundations of Python programming and learn how Python can be used to achieve results.

This third edition is updated with TensorFlow 2 and the latest additions to scikit-learn. Packed with clear explanations, visualizations, and working examples, the book covers essential machine learning techniques in depth, along with two cutting-edge machine learning techniques: reinforcement learning and generative adversarial networks.

With six new chapters, Deep Reinforcement Learning Hands-On Second edition is completely updated and expanded with the very latest reinforcement learning (RL) tools and techniques, providing you with an introduction to RL, as well as the hands-on ability to code intelligent learning agents to perform a range of practical tasks.

Being familiar with object-oriented design is an essential part of programming in Python. This new edition includes all the topics that made Python Object-Oriented Programming an instant Packt classic. Moreover, it’s packed with updated content to reflect more recent changes in the core Python libraries and cover modern third-party packages.

Modern Time Series Forecasting with Python is a timely book that goes beyond popular classical time series techniques such as ARIMA and exponential smoothing and embraces modern high-performant techniques like machine learning. You’ll discover tested tips and tricks to advance your skillset and make you industry-ready in time series forecasting.

Explore recipes for both classical quantitative finance approaches to modeling financial data, as well as modern machine learning and deep learning solutions

The new edition is revised and updated with Python 3.10 along with new chapters on AsyncIO and Docker containers. The book will provide examples and guidance to manage your network, improve reliability, and simplify your task. The fourth edition also includes network context examples of Ansible, Flask, Elasticsearch, Git, GitLab and more.

Algorithms play an important role in computing, so a deeper understanding of an algorithm's logic and mathematics is essential. Beyond traditional computing, being able to apply these algorithms to real-world problems is a necessary skill and what this book focuses on.

With this book, you’ll navigate the intricacies of data serialization. From understanding syntax nuances to mastering schema evolution and customizations, you’ll seamlessly integrate Protobuf across languages and construct data-driven systems.

Official pandas documentation, while thorough, does not contain many useful examples. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter.