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How will variation in the actual durations of each activity be dealt with to ensure that the expected Python results are met? Who will be responsible for deciding whether Python goes ahead or not after the initial investigations? Design Thinking: Integrating Innovation, Python Experience, and Brand Value What is our Python Strategy? Are assumptions made in Python stated explicitly? This extraordinary Python self-assessment will make you the established Python domain visionary by revealing just what you need to know to be fluent and ready for any Python challenge. How do I reduce the effort in the Python work to be done to get problems solved? How can I ensure that plans of action include every Python task and that every Python outcome is in place? How will I save time investigating strategic and tactical options and ensuring Python costs are low? How can I deliver tailored Python advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Python essentials are covered, from every angle: the Python self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Python outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Python practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Python are maximized with professional results. Your purchase includes access details to the Python self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard, and... - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation ...plus an extra, special, resource that helps you with project managing. INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Already the industry standard for Python users, ProgrammingPython fromO'Reilly just got even better. This third edition has been updated toreflect current best practices andthe abundance of changes introduced by the latest version of thelanguage, Python 2.5. Whether you're a novice or an advancedpractitioner, you'll find thisrefreshed book more than lives up to its reputation. ProgrammingPython, 3rd Edition, teaches you the rightway to code. It explains Python language syntax and programmingtechniques in a clear and concisemanner, with numerous examples that illustrate both correct usage andcommon idioms. By reading thiscomprehensive guide, you'll learn how to apply Python in real-worldproblem domains such as: GUI programming Internet scripting Parallel processing Database management Networked applications Programming Python, Third Edition coverseach of thesetarget domainsgradually, beginning with in-depth discussions of core concepts andthen progressing toward completeprograms. Large examples do appear, but only after you've learnedenough to understand their techniques andcode. Along the way, you'll also learn how to use the Python language inrealistically scaled programs--concepts such as Object-Oriented Programming (OOP) and code reuseare recurring side themes throughout thistext. If you're interested in Python programming, then this O'Reillyclassic needs to be within arm's reach. Thewealth of practical advice, snippets of code, and patterns of programdesign can all be put into use on adaily basis--making your life easier and more productive. Reviews of the second edition: "...about as comprehensive as any book can be." --Dr. Dobb's Journal "If the language had manuals, they would undoubtedlybe the texts from O'Reilly...'Learning Python' and 'Programming Python'are definitive treatments." --SD Times
Google and YouTube use Python because it's highly adaptable, easy to maintain, and allows for rapid development. If you want to write high-quality, efficient code that's easily integrated with other languages and tools, this hands-on book will help you be productive with Python quickly -- whether you're new to programming or just new to Python. It's an easy-to-follow self-paced tutorial, based on author and Python expert Mark Lutz's popular training course. Each chapter contains a stand-alone lesson on a key component of the language, and includes a unique Test Your Knowledge section with practical exercises and quizzes, so you can practice new skills and test your understanding as you go. You'll find lots of annotated examples and illustrations to help you get started with Python 3.0. Learn about Python's major built-in object types, such as numbers, lists, and dictionaries Create and process objects using Python statements, and learn Python's general syntax model Structure and reuse code using functions, Python's basic procedural tool Learn about Python modules: packages of statements, functions, and other tools, organized into larger components Discover Python's object-oriented programming tool for structuring code Learn about the exception-handling model, and development tools for writing larger programs Explore advanced Python tools including decorators, descriptors, metaclasses, and Unicode processing
With a primary focus on examples and applications of relevance to computational scientists, this brilliantly useful book shows computational scientists how to develop tailored, flexible, and human-efficient working environments built from small scripts written in the easy-to-learn, high-level Python language. All the tools and examples in this book are open source codes. This third edition features lots of new material. It is also released after a comprehensive reorganization of the text. The author has inserted improved examples and tools and updated information, as well as correcting any errors that crept in to the first imprint.
If you are new to programming with Python and are looking for a solid introduction, this is the book for you. Developed by computer science instructors, books in the "for the absolute beginner" series teach the principles of programming through simple gam
Get more from your data by creating practical machine learning systems with Python Key Features Develop your own Python-based machine learning system Discover how Python offers multiple algorithms for modern machine learning systems Explore key Python machine learning libraries to implement in your projects Book Description Machine learning allows systems to learn things without being explicitly programmed to do so. Python is one of the most popular languages used to develop machine learning applications, which take advantage of its extensive library support. This third edition of Building Machine Learning Systems with Python addresses recent developments in the field by covering the most-used datasets and libraries to help you build practical machine learning systems. Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python, being a dynamic language, allows for fast exploration and experimentation. This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and being introduced to libraries. You'll quickly get to grips with serious, real-world projects on datasets, using modeling and creating recommendation systems. With Building Machine Learning Systems with Python, you’ll gain the tools and understanding required to build your own systems, all tailored to solve real-world data analysis problems. By the end of this book, you will be able to build machine learning systems using techniques and methodologies such as classification, sentiment analysis, computer vision, reinforcement learning, and neural networks. What you will learn Build a classification system that can be applied to text, images, and sound Employ Amazon Web Services (AWS) to run analysis on the cloud Solve problems related to regression using scikit-learn and TensorFlow Recommend products to users based on their past purchases Understand different ways to apply deep neural networks on structured data Address recent developments in the field of computer vision and reinforcement learning Who this book is for Building Machine Learning Systems with Python is for data scientists, machine learning developers, and Python developers who want to learn how to build increasingly complex machine learning systems. You will use Python's machine learning capabilities to develop effective solutions. Prior knowledge of Python programming is expected.

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