Learn Python fundamentals that can be used in any programming setting – use the guidance in this book to program your own game in a unique and practical Python learning experience. Learning Python opens the door to a world of programming possibilities. From AI and machine learning to video game, app, and web development, Python is a critical behind-the-scenes component of everyday technology. Python powers the services of household names like Google, Netflix, and Spotify along with tech pioneers like NASA, IBM, and Intel. Put simply, Python is the in-demand and easy-to-learn programming language that gets stuff done. In Python QuickStart Guide, senior developer and programmer Robert Oliver lays out the quickest and most accessible path yet to the mastery of Python fundamentals. Distilling his experience drawn from over two decades of working with Python and other programming languages, Robert’s clear voice and writing present a practical, hands-on approach that anyone, at any experience level, can use to become a Python programmer. It doesn’t matter if you are a new or existing programmer, a job seeker looking for a career change or promotion, or just someone who wants to learn how to automate basic tasks with Python—Robert’s step-by-step approach, complete with a hands-on companion Python game project, is the perfect starting point to master Python fundamentals! Python QuickStart Guide is Perfect for: - New or experienced programmers looking to enhance their career opportunities with an in-demand programming language - Job seekers who want to supercharge their resumes and increase their value in the job marketplace - Students or recent college grads who have their sights set on a lucrative position in the tech industry - Full stack developers or programmers who need to round out their programming skills to take on new projects - Coding or programming bootcamp students looking for supplemental learning material - Anyone who wants to explore the world of programming, use Python to automate tedious tasks, or enhance their resume and future-proof their skills! Python QuickStart Guide Explains - The best practical approach to learning Python—follow along with the exercises in the book to program your own video game and learn along the way - How to master Python building blocks and build a robust set of programming skills at your own pace - How to avoid common pitfalls new programmers face, how to debug code, and how to eliminate frustrating errors - Coding best practices that anyone can use to level up their programming skills using Python or any other programming language You Will Learn - How to Use Python – Practical Examples, Code Snippets, Plus Follow Along to Code Your Own Game! - Python Fundamentals – How to Use Python for Web Design and Interfacing with GitHub, SQL, and Other Applications - Object-Oriented Programming Principles – Managing Data, Scripts, Logic, Inputs, Outputs, and More! - Programming Essentials – Debugging, Producing Clean Code, Best Practices, Time-Savers, and Tips - Python Next Steps –Testing, Optimization, Speed Improvements, Integrations with Other Applications, and More! *Lifetime Access To Free Python Programming Digital Assets* In addition to the follow-along Python game included with the exercises in the book, Python QuickStart Guide comes with a library of references and cheat sheets to help you go beyond the book and get the most out of your Python learning experience. QuickStart Guides are books for beginners, written by experts. *Giving Back* QuickStart Guides plants trees in areas where they are needed most with the help of our reforestation partner One Tree Planted.

Python is a remarkably powerful dynamic programming language that is used in a wide variety of application domains such as Web, database access, desktop GUIs, game and software development, and network programming. Fans of Python use the phrase "batteries included" to describe the standard library, which covers everything from asynchronous processing to zip files. The language itself is a flexible powerhouse that can handle practically any application domain. This task-based tutorial is for students with no programming experience as well as those programmers who have some experience with the programming language and now want to take their skills to the next level. The book walks a reader through all the fundamentals and then moves on to more advanced topics. It's a complete end-to-end tutorial and reference.

A comprehensive guide to help you understand the principles of Reactive and asynchronous programming and its benefits Key FeaturesExplore the advantages of Reactive programmingUse concurrency and parallelism in RxPY to build powerful reactive applicationsDeploy and scale your reactive applications using DockerBook Description Reactive programming is central to many concurrent systems, but it’s famous for its steep learning curve, which makes most developers feel like they're hitting a wall. With this book, you will get to grips with reactive programming by steadily exploring various concepts This hands-on guide gets you started with Reactive Programming (RP) in Python. You will learn abouta the principles and benefits of using RP, which can be leveraged to build powerful concurrent applications. As you progress through the chapters, you will be introduced to the paradigm of Functional and Reactive Programming (FaRP), observables and observers, and concurrency and parallelism. The book will then take you through the implementation of an audio transcoding server and introduce you to a library that helps in the writing of FaRP code. You will understand how to use third-party services and dynamically reconfigure an application. By the end of the book, you will also have learned how to deploy and scale your applications with Docker and Traefik and explore the significant potential behind the reactive streams concept, and you'll have got to grips with a comprehensive set of best practices. What you will learnStructure Python code for better readability, testing, and performanceExplore the world of event-based programmingGrasp the use of the most common operators in RxUnderstand reactive extensions beyond simple examplesMaster the art of writing reusable componentsDeploy an application on a cloud platform with Docker and TraefikWho this book is for If you are a Python developer who wants to learn Reactive programming to build powerful concurrent and asynchronous applications, this book is for you. Basic understanding of the Python language is all you need to understand the concepts covered in this book.

The Hitchhiker's Guide to Python takes the journeyman Pythonista to true expertise. More than any other language, Python was created with the philosophy of simplicity and parsimony. Now 25 years old, Python has become the primary or secondary language (after SQL) for many business users. With popularity comes diversityâ??and possibly dilution. This guide, collaboratively written by over a hundred members of the Python community, describes best practices currently used by package and application developers. Unlike other books for this audience, The Hitchhikerâ??s Guide is light on reusable code and heavier on design philosophy, directing the reader to excellent sources that already exist.

Named after the Monty Python comedy troupe, Python is an interpreted, open-source, object-oriented programming language. It's also free and runs portably on Windows, Mac OS, Unix, and other operating systems. Python can be used for all manner of programming tasks, from CGI scripts to full-fledged applications. It is gaining popularity among programmers in part because it is easier to read (and hence, debug) than most other programming languages, and it's generally simpler to install, learn, and use. Its line structure forces consistent indentation. Its syntax and semantics make it suitable for simple scripts and large programs. Its flexible data structures and dynamic typing allow you to get a lot done in a few lines. To learn it, you'll need is some basic programming experience and a copy of Python: Visual QuickStart Guide. In patented Visual QuickStart Guide fashion, the book doesn't just tell you how to use Python to develop applications, it shows you, breaking Python into easy-to-digest, step-by-step tasks and providing example code. Python: Visual QuickStart Guide emphasizes the core language and libraries, which are the building blocks for programs. Author Chris Fehily starts with the basics - expressions, statements, numbers, strings - then moves on to lists, dictionaries, functions, and modules before wrapping things up with straightforward discussions of exceptions and classes. Some additional topics covered include: - Object-oriented programming- Working in multiple operating systems- Structuring large programs- Comparing Python to C, Perl, and Java- Handling errors gracefully.

Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media—including who’s connecting with whom, what they’re talking about, and where they’re located—using Python code examples, Jupyter notebooks, or Docker containers. In part one, each standalone chapter focuses on one aspect of the social landscape, including each of the major social sites, as well as web pages, blogs and feeds, mailboxes, GitHub, and a newly added chapter covering Instagram. Part two provides a cookbook with two dozen bite-size recipes for solving particular issues with Twitter. Get a straightforward synopsis of the social web landscape Use Docker to easily run each chapter’s example code, packaged as a Jupyter notebook Adapt and contribute to the code’s open source GitHub repository Learn how to employ best-in-class Python 3 tools to slice and dice the data you collect Apply advanced mining techniques such as TFIDF, cosine similarity, collocation analysis, clique detection, and image recognition Build beautiful data visualizations with Python and JavaScript toolkits

This hands-on guide to optimizing web sites for Google Glass will show you how to take advantage of the latest advancements of this tiny screen, including watching videos and viewing forms. You'll also take a look at the Mirror API and building web-based native apps for Google Glass, and get insightful tips from an expert designer on avoiding web design pitfalls.

Get hands-on experience in creating state-of-the-art reinforcement learning agents using TensorFlow and RLlib to solve complex real-world business and industry problems with the help of expert tips and best practices Key FeaturesUnderstand how large-scale state-of-the-art RL algorithms and approaches workApply RL to solve complex problems in marketing, robotics, supply chain, finance, cybersecurity, and moreExplore tips and best practices from experts that will enable you to overcome real-world RL challengesBook Description Reinforcement learning (RL) is a field of artificial intelligence (AI) used for creating self-learning autonomous agents. Building on a strong theoretical foundation, this book takes a practical approach and uses examples inspired by real-world industry problems to teach you about state-of-the-art RL. Starting with bandit problems, Markov decision processes, and dynamic programming, the book provides an in-depth review of the classical RL techniques, such as Monte Carlo methods and temporal-difference learning. After that, you will learn about deep Q-learning, policy gradient algorithms, actor-critic methods, model-based methods, and multi-agent reinforcement learning. Then, you'll be introduced to some of the key approaches behind the most successful RL implementations, such as domain randomization and curiosity-driven learning. As you advance, you’ll explore many novel algorithms with advanced implementations using modern Python libraries such as TensorFlow and Ray’s RLlib package. You’ll also find out how to implement RL in areas such as robotics, supply chain management, marketing, finance, smart cities, and cybersecurity while assessing the trade-offs between different approaches and avoiding common pitfalls. By the end of this book, you’ll have mastered how to train and deploy your own RL agents for solving RL problems. What you will learnModel and solve complex sequential decision-making problems using RLDevelop a solid understanding of how state-of-the-art RL methods workUse Python and TensorFlow to code RL algorithms from scratchParallelize and scale up your RL implementations using Ray's RLlib packageGet in-depth knowledge of a wide variety of RL topicsUnderstand the trade-offs between different RL approachesDiscover and address the challenges of implementing RL in the real worldWho this book is for This book is for expert machine learning practitioners and researchers looking to focus on hands-on reinforcement learning with Python by implementing advanced deep reinforcement learning concepts in real-world projects. Reinforcement learning experts who want to advance their knowledge to tackle large-scale and complex sequential decision-making problems will also find this book useful. Working knowledge of Python programming and deep learning along with prior experience in reinforcement learning is required.

Learn to implement complex data structures and algorithms using Python Key FeaturesUnderstand the analysis and design of fundamental Python data structuresExplore advanced Python concepts such as Big O notation and dynamic programmingLearn functional and reactive implementations of traditional data structuresBook Description Data structures allow you to store and organize data efficiently. They are critical to any problem, provide a complete solution, and act like reusable code. Hands-On Data Structures and Algorithms with Python teaches you the essential Python data structures and the most common algorithms for building easy and maintainable applications. This book helps you to understand the power of linked lists, double linked lists, and circular linked lists. You will learn to create complex data structures, such as graphs, stacks, and queues. As you make your way through the chapters, you will explore the application of binary searches and binary search trees, along with learning common techniques and structures used in tasks such as preprocessing, modeling, and transforming data. In the concluding chapters, you will get to grips with organizing your code in a manageable, consistent, and extendable way. You will also study how to bubble sort, selection sort, insertion sort, and merge sort algorithms in detail. By the end of the book, you will have learned how to build components that are easy to understand, debug, and use in different applications. You will get insights into Python implementation of all the important and relevant algorithms. What you will learnUnderstand object representation, attribute binding, and data encapsulationGain a solid understanding of Python data structures using algorithmsStudy algorithms using examples with pictorial representationLearn complex algorithms through easy explanation, implementing PythonBuild sophisticated and efficient data applications in PythonUnderstand common programming algorithms used in Python data scienceWrite efficient and robust code in Python 3.7Who this book is for This book is for developers who want to learn data structures and algorithms in Python to write complex and flexible programs. Basic Python programming knowledge is expected.

Unmanned aerial systems (UAS) have evolved rapidly in recent years thanks to advances in microelectromechanical components, navigation, perception, and artificial intelligence, allowing for a fast development of autonomy. This book presents general approaches to develop, test, and evaluate critical functions such as navigation, obstacle avoidance and perception, and the capacity to improve performance in real and simulated scenarios. It provides the practical knowledge to install, analyze and evaluate UAS solutions working in real systems; illustrates how to use and configure complete platforms and software tools; and reviews the main enabling technologies applied to develop UAS, possibilities and evaluation methodology. You will get the tools you need to evaluate navigation and obstacle avoidance functions, object detection, and planning and landing alternatives in simulated conditions. The book also provides helpful guidance on the integration of additional sensors (video, weather, meteorological) and communication networks to build IoT solutions. This is an important book for practitioners and researchers interested in integrating advanced techniques in the fields of AI, sensor fusion and mission management, and anyone interest in applying and testing advanced algorithms in UAS platforms.