Products related to Python:
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Learning Python
Get a comprehensive, in-depth introduction to the core Python language with this hands-on book.Based on author Mark Lutz's popular training course, this updated fifth edition will help you quickly write efficient, high-quality code with Python.It's an ideal way to begin, whether you're new to programming or a professional developer versed in other languages.Complete with quizzes, exercises, and helpful illustrations, this easy-to-follow, self-paced tutorial gets you started with both Python 2.7 and 3.3 - the latest releases in the 3.X and 2.X lines - plus all other releases in common use today.You'll also learn some advanced language features that recently have become more common in Python code.Explore Python's major built-in object types such as numbers, lists, and dictionaries Create and process objects with Python statements, and learn Python's general syntax model Use functions to avoid code redundancy and package code for reuse Organize statements, functions, and other tools into larger components with modules Dive into classes: Python's object-oriented programming tool for structuring code Write large programs with Python's exception-handling model and development tools Learn advanced Python tools, including decorators, descriptors, metaclasses, and Unicode processing
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Teaching, Tutoring and Training in the Lifelong Learning Sector
This core text provides comprehensive support for pre-service and in-service trainee teachers in the Lifelong Learning Sector covering all they need to know to achieve QTLS status. Supporting trainees through all stages of their professional development, the text takes the reader through the theoretical background underpinning teaching and learning and offers practical guidance on day-to-day challenges. This fourth edition has been fully revised and updated and includes a new chapter on teaching practice with notes on observation and lesson planning.New information on behaviour management has been added to support trainees in an aspect of teaching that many find challenging.
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Python Machine Learning
Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This Book• Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization• Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms• Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasetsWho This Book Is ForIf you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn• Explore how to use different machine learning models to ask different questions of your data• Learn how to build neural networks using Keras and Theano• Find out how to write clean and elegant Python code that will optimize the strength of your algorithms• Discover how to embed your machine learning model in a web application for increased accessibility• Predict continuous target outcomes using regression analysis• Uncover hidden patterns and structures in data with clustering• Organize data using effective pre-processing techniques• Get to grips with sentiment analysis to delve deeper into textual and social media dataIn DetailMachine learning and predictive analytics are transforming the way businesses and other organizations operate.Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace.Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages.If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable.Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approachPython Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions.It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.
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Pragmatic Python Programming : Learning Python the Smart Way
Explore the world of programming languages through Python and learn the building blocks of writing programs.This book covers Python 3.10, explaining it through six key concepts.Each chapter contains a real-world example with practical advice and a section on advanced concepts. You'll start by reviewing the concept of expressions and functions, which are two of the core building blocks of programming languages. You'll then move on to object-oriented concepts to help gain a practical understanding of Python, along with a chapter on control flow constructs.The book also takes a close look at sequences, explaining constructs and additional types, and wraps up with a chapter on modules, focusing on how to use and create packages. Whether you’re new to programming or already an experienced developer, upon finishing this book, you will have a solid understanding of Python's state-of-the-art development features. What You Will LearnStudy the six main concepts of the programming languagesLearn how to use programming language constructs through examplesReview the core Python language notations and concepts. Start using Python as a working languageWho This Book Is ForSoftware developers wanting to gain professional core Python knowledge quickly, and non-developers wanting to gain an understanding of programming concepts.
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What is the Python learning environment?
The Python learning environment refers to the tools and resources available for individuals to learn and practice Python programming. This includes online tutorials, interactive coding platforms, textbooks, and IDEs (Integrated Development Environments) such as PyCharm, Jupyter Notebook, and Visual Studio Code. These environments provide a platform for beginners to write, test, and debug Python code, helping them to develop their programming skills effectively.
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Is one learning Python, or not?
It is not clear from the question whether someone is learning Python or not. More information is needed to determine if the person in question is currently learning Python or not.
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Is Python worth learning, or not?
Yes, Python is definitely worth learning. It is a versatile and beginner-friendly programming language that is widely used in various fields such as web development, data science, artificial intelligence, and automation. Python's simple syntax and readability make it a great choice for both beginners and experienced programmers. Additionally, there is a large and active community of Python developers who contribute to its extensive library of modules and resources, making it a valuable skill to have in today's job market.
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Is it worth learning Python or not?
Yes, it is definitely worth learning Python. Python is a versatile and powerful programming language that is widely used in various fields such as web development, data science, artificial intelligence, and automation. It has a simple and readable syntax, making it easy for beginners to learn. Additionally, Python has a large and active community that provides support and resources for learning and development. Overall, learning Python can open up a wide range of opportunities and enhance your skills as a programmer.
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Deep Learning with Python
"The first edition of Deep Learning with Python is one of the best books on the subject.The second edition made it even better." - Todd Cook The bestseller revised!Deep Learning with Python, Second Edition is a comprehensive introduction to the field of deep learning using Python and the powerful Keras library.Written by Google AI researcher François Chollet, the creator of Keras, this revised edition has been updated with new chapters, new tools, and cutting-edge techniques drawn from the latest research.You'll build your understanding through practical examples and intuitive explanations that make the complexities of deep learning accessible and understandable. about the technologyMachine learning has made remarkable progress in recent years.We've gone from near-unusable speech recognition, to near-human accuracy.From machines that couldn't beat a serious Go player, to defeating a world champion.Medical imaging diagnostics, weather forecasting, and natural language question answering have suddenly become tractable problems.Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications across every industry sector about the bookDeep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library.You'll learn directly from the creator of Keras, François Chollet, building your understanding through intuitive explanations and practical examples.Updated from the original bestseller with over 50% new content, this second edition includes new chapters, cutting-edge innovations, and coverage of the very latest deep learning tools.You'll explore challenging concepts and practice with applications in computer vision, natural-language processing, and generative models.By the time you finish, you'll have the knowledge and hands-on skills to apply deep learning in your own projects. what's insideDeep learning from first principlesImage-classification, imagine segmentation, and object detectionDeep learning for natural language processingTimeseries forecastingNeural style transfer, text generation, and image generation about the readerReaders need intermediate Python skills.No previous experience with Keras, TensorFlow, or machine learning is required. about the authorFrançois Chollet works on deep learning at Google in Mountain View, CA.He is the creator of the Keras deep-learning library, as well as a contributor to the TensorFlow machine-learning framework.He also does AI research, with a focus on abstraction and reasoning.His papers have been published at major conferences in the field, including the Conference on Computer Vision and Pattern Recognition (CVPR), the Conference and Workshop on Neural Information Processing Systems (NIPS), the International Conference on Learning Representations (ICLR), and others.
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Python Machine Learning : Machine Learning and Deep Learning with Python, scikit-learn, and TensorFlow 2
Applied machine learning with a solid foundation in theory.Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key FeaturesThird edition of the bestselling, widely acclaimed Python machine learning bookClear and intuitive explanations take you deep into the theory and practice of Python machine learningFully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practicesBook DescriptionPython Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python.It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems. Packed with clear explanations, visualizations, and working examples, the book covers all the essential machine learning techniques in depth.While some books teach you only to follow instructions, with this machine learning book, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn.It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs.Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents. This book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments. What you will learnMaster the frameworks, models, and techniques that enable machines to 'learn' from dataUse scikit-learn for machine learning and TensorFlow for deep learningApply machine learning to image classification, sentiment analysis, intelligent web applications, and moreBuild and train neural networks, GANs, and other modelsDiscover best practices for evaluating and tuning modelsPredict continuous target outcomes using regression analysisDig deeper into textual and social media data using sentiment analysisWho this book is forIf you know some Python and you want to use machine learning and deep learning, pick up this book.Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource.Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.
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Learning to Program in Python
This book is intended for individuals and students learning to program.You may already have done some programming in other languages, but not be familiar with Python.Novice programmers should work through the book sequentially, starting at Chapter 1.It will also be a useful reference book for students on a programming course or anyone working on a programming project.It teaches basic syntax and programming techniques, and introduces three inbuilt Python modules: "> Tkinter, used for building a graphical user interface, which is an option that some users may like to include in their project work. "> SQLite, which enables the creation and processing of a database from within a Python program.This provides an alternative to writing to a text file when data needs to be stored and retrieved "> .pdb, Python's debugging module, which can be used to help find elusive logic errors. Questions and exercises are included in every chapter.Answers to these as well as over 120 Python programs for all the examples and exercises given in the book may be downloaded from www.pgonline.co.uk. These programs enable users of the book to try out the in-text examples and check possible solutions to the exercises.
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Learning Data Mining with Python
COM051360
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Which book is suitable for learning Python?
One highly recommended book for learning Python is "Python Crash Course" by Eric Matthes. This book is suitable for beginners as it covers the basics of Python programming in a clear and concise manner. It includes hands-on projects and exercises to help reinforce learning. Additionally, the book covers both fundamental concepts and more advanced topics, making it a comprehensive resource for anyone looking to learn Python.
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What comes after learning the basics of Python?
After learning the basics of Python, the next step is to deepen your understanding of the language by exploring more advanced topics such as object-oriented programming, data structures, algorithms, and libraries like NumPy, Pandas, and Matplotlib for data analysis and visualization. Additionally, you can start working on real-world projects to apply your knowledge and gain practical experience. It's also beneficial to learn about software development best practices, version control systems, and how to collaborate with others using tools like Git and GitHub. Finally, you can consider exploring other related technologies and languages, such as web development with frameworks like Django or Flask, or diving into machine learning and artificial intelligence with libraries like TensorFlow and PyTorch.
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Which book is the best for learning Python?
The best book for learning Python is subjective and depends on the individual's learning style and level of expertise. However, "Python Crash Course" by Eric Matthes is highly recommended for beginners as it covers the fundamentals of Python programming in a clear and engaging manner. For more experienced programmers, "Fluent Python" by Luciano Ramalho provides a deeper understanding of Python's features and best practices. Ultimately, it's important to choose a book that aligns with your learning goals and preferences.
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What are the prerequisites for Deep Learning with Python?
The prerequisites for Deep Learning with Python include a solid understanding of Python programming language, familiarity with basic machine learning concepts, such as neural networks and optimization algorithms, and knowledge of linear algebra and calculus. Additionally, having experience with libraries such as NumPy, Pandas, and Matplotlib can be beneficial for data manipulation and visualization tasks. Finally, a strong foundation in statistics and probability theory is also recommended for understanding the underlying principles of deep learning algorithms.
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