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Author: Mark Lutz
Publisher: "O'Reilly Media, Inc."
ISBN: 1449355692
Category : Computers
Languages : en
Pages : 1740
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Book Description
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
Author: Mark Lutz
Publisher: "O'Reilly Media, Inc."
ISBN: 1449355692
Category : Computers
Languages : en
Pages : 1740
Get Book Here
Book Description
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
Author: Adrienne B. Tacke
Publisher: Sourcebooks, Inc.
ISBN: 1641521767
Category : Juvenile Nonfiction
Languages : en
Pages : 329
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Book Description
Games and activities that teach kids ages 10+ to code with Python Learning to code isn't as hard as it sounds—you just have to get started! Coding for Kids: Python starts kids off right with 50 fun, interactive activities that teach them the basics of the Python programming language. From learning the essential building blocks of programming to creating their very own games, kids will progress through unique lessons packed with helpful examples—and a little silliness! Kids will follow along by starting to code (and debug their code) step by step, seeing the results of their coding in real time. Activities at the end of each chapter help test their new knowledge by combining multiple concepts. For young programmers who really want to show off their creativity, there are extra tricky challenges to tackle after each chapter. All kids need to get started is a computer and this book. This beginner's guide to Python for kids includes: 50 Innovative exercises—Coding concepts come to life with game-based exercises for creating code blocks, drawing pictures using a prewritten module, and more. Easy-to-follow guidance—New coders will be supported by thorough instructions, sample code, and explanations of new programming terms. Engaging visual lessons—Colorful illustrations and screenshots for reference help capture kids' interest and keep lessons clear and simple. Encourage kids to think independently and have fun learning an amazing new skill with this coding book for kids.
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book Description
An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance, marketing, and astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Jake VanderPlas
Publisher: "O'Reilly Media, Inc."
ISBN: 1491912138
Category : Computers
Languages : en
Pages : 609
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Book Description
For many researchers, Python is a first-class tool mainly because of its libraries for storing, manipulating, and gaining insight from data. Several resources exist for individual pieces of this data science stack, but only with the Python Data Science Handbook do you get them all—IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and other related tools. Working scientists and data crunchers familiar with reading and writing Python code will find this comprehensive desk reference ideal for tackling day-to-day issues: manipulating, transforming, and cleaning data; visualizing different types of data; and using data to build statistical or machine learning models. Quite simply, this is the must-have reference for scientific computing in Python. With this handbook, you’ll learn how to use: IPython and Jupyter: provide computational environments for data scientists using Python NumPy: includes the ndarray for efficient storage and manipulation of dense data arrays in Python Pandas: features the DataFrame for efficient storage and manipulation of labeled/columnar data in Python Matplotlib: includes capabilities for a flexible range of data visualizations in Python Scikit-Learn: for efficient and clean Python implementations of the most important and established machine learning algorithms
Author: Francois Chollet
Publisher: Simon and Schuster
ISBN: 1638352046
Category : Computers
Languages : en
Pages : 597
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Book Description
Summary Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning has made remarkable progress in recent years. We went from near-unusable speech and image recognition, to near-human accuracy. We went from machines that couldn't beat a serious Go player, to defeating a world champion. Behind this progress is deep learning—a combination of engineering advances, best practices, and theory that enables a wealth of previously impossible smart applications. About the Book Deep Learning with Python introduces the field of deep learning using the Python language and the powerful Keras library. Written by Keras creator and Google AI researcher François Chollet, this book builds your understanding through intuitive explanations and practical examples. 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 Inside Deep learning from first principles Setting up your own deep-learning environment Image-classification models Deep learning for text and sequences Neural style transfer, text generation, and image generation About the Reader Readers need intermediate Python skills. No previous experience with Keras, TensorFlow, or machine learning is required. About the Author François 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 deep-learning research, with a focus on computer vision and the application of machine learning to formal 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. Table of Contents PART 1 - FUNDAMENTALS OF DEEP LEARNING What is deep learning? Before we begin: the mathematical building blocks of neural networks Getting started with neural networks Fundamentals of machine learning PART 2 - DEEP LEARNING IN PRACTICE Deep learning for computer vision Deep learning for text and sequences Advanced deep-learning best practices Generative deep learning Conclusions appendix A - Installing Keras and its dependencies on Ubuntu appendix B - Running Jupyter notebooks on an EC2 GPU instance
Author: Charles R. Severance
Publisher:
ISBN: 9781530051120
Category :
Languages : en
Pages : 242
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Book Description
Python for Everybody is designed to introduce students to programming and software development through the lens of exploring data. You can think of the Python programming language as your tool to solve data problems that are beyond the capability of a spreadsheet.Python is an easy to use and easy to learn programming language that is freely available on Macintosh, Windows, or Linux computers. So once you learn Python you can use it for the rest of your career without needing to purchase any software.This book uses the Python 3 language. The earlier Python 2 version of this book is titled "Python for Informatics: Exploring Information".There are free downloadable electronic copies of this book in various formats and supporting materials for the book at www.pythonlearn.com. The course materials are available to you under a Creative Commons License so you can adapt them to teach your own Python course.
Author: Diego Rodrigues
Publisher: Diego Rodrigues
ISBN:
Category : Computers
Languages : en
Pages : 294
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Book Description
🚀 TAKE ADVANTAGE OF THE PROMOTIONAL LAUNCH PRICE OF THE YEAR 🚀 Become a Python expert with "40 Python Libraries: An Essential Guide for Students and Professionals - 2024 Edition". This guide by Diego Rodrigues is a must-have for students, developers, and professionals who want to master Python and its practical applications. Dive into the Python ecosystem by exploring powerful libraries. Use NumPy for scientific computing, Pandas for data analysis, Matplotlib and Seaborn for visualization, Scikit-learn for machine learning, TensorFlow and Keras for deep learning. Web development becomes easy with Flask and Django, while Requests and BeautifulSoup simplify web scraping. Enhance computer vision skills with OpenCV and Pillow, and develop games with PyGame. Discover SciPy for scientific computing and SymPy for symbolic mathematics. Use Statsmodels for data analysis and visualize interactively with Plotly and Bokeh. Explore NLP with NLTK and spaCy, neural networks with PyTorch, graph analysis with NetworkX, and data mining with Scrapy. SQLAlchemy optimizes databases, Celery for parallel processing, and PandasQL integrates SQL with DataFrames. Handle big data with Dask, test software with PyTest, and use Jupyter for interactive notebooks. Leverage Hadoop and Spark for Big Data, and Kivy and Tkinter for graphical interfaces. Apply these libraries to practical projects: analyzing large datasets, building predictive models, developing web and mobile applications, automating tasks, and integrating with platforms like AWS, Google Cloud, and Microsoft Azure. With this book, acquire the skills to innovate and lead in the competitive tech world, tackling challenges efficiently. Transform your skills into a strategic advantage. This practical, results-focused book accelerates your learning and boosts your career. Get your copy and start mastering Python and its libraries, turning challenges into effective solutions. Python programming, scientific computing, data analysis, visualization, machine learning, artificial intelligence, neural networks, automation, web development, cybersecurity, big data, software engineering, computer science, statistical analysis, data mining, machine learning, deep learning, web frameworks, RESTful APIs, cloud computing, technological innovation, operational efficiency, data science, computer vision, natural language processing, IoT, cloud security, DevOps, predictive analytics, Docker, Kubernetes, Hadoop, Spark, SQL, NoSQL, sentiment analysis, A/B testing, predictive modeling, systems design, prototyping, SCRUM, Agile, project management, business analysis. Tags: Python NumPy Pandas Matplotlib Seaborn Scikit-learn TensorFlow Keras Flask Django Requests BeautifulSoup OpenCV Pillow PyGame SciPy SymPy Statsmodels Plotly Bokeh NLTK spaCy PyTorch NetworkX Scrapy SQLAlchemy Celery PandasQL Dask PyTest Jupyter Hadoop Spark Kivy Tkinter automation scientific computing data visualization artificial intelligence neural networks machine learning deep learning big data data analysis computer science software engineering cybersecurity AWS Google Cloud Microsoft Azure RESTful APIs Python programming technological innovation operational efficiency computer vision natural language processing IoT cloud security DevOps predictive analytics Docker Kubernetes SQL NoSQL sentiment analysis A/B testing predictive modeling systems design prototyping SCRUM Agile project management business analysis Diego Rodrigues
Author: Zed A. Shaw
Publisher: Addison-Wesley Professional
ISBN: 0134693906
Category : Computers
Languages : en
Pages : 752
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Book Description
You Will Learn Python 3! Zed Shaw has perfected the world’s best system for learning Python 3. Follow it and you will succeed—just like the millions of beginners Zed has taught to date! You bring the discipline, commitment, and persistence; the author supplies everything else. In Learn Python 3 the Hard Way, you’ll learn Python by working through 52 brilliantly crafted exercises. Read them. Type their code precisely. (No copying and pasting!) Fix your mistakes. Watch the programs run. As you do, you’ll learn how a computer works; what good programs look like; and how to read, write, and think about code. Zed then teaches you even more in 5+ hours of video where he shows you how to break, fix, and debug your code—live, as he’s doing the exercises. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Variables Strings and text Interact with users Work with files Looping and logic Data structures using lists and dictionaries Program design Object-oriented programming Inheritance and composition Modules, classes, and objects Python packaging Automated testing Basic game development Basic web development It’ll be hard at first. But soon, you’ll just get it—and that will feel great! This course will reward you for every minute you put into it. Soon, you’ll know one of the world’s most powerful, popular programming languages. You’ll be a Python programmer. This Book Is Perfect For Total beginners with zero programming experience Junior developers who know one or two languages Returning professionals who haven’t written code in years Seasoned professionals looking for a fast, simple, crash course in Python 3
Author: Bill Lubanovic
Publisher: "O'Reilly Media, Inc."
ISBN: 1492051322
Category : Computers
Languages : en
Pages : 630
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Book Description
Easy to understand and fun to read, this updated edition of Introducing Python is ideal for beginning programmers as well as those new to the language. Author Bill Lubanovic takes you from the basics to more involved and varied topics, mixing tutorials with cookbook-style code recipes to explain concepts in Python 3. End-of-chapter exercises help you practice what you’ve learned. You’ll gain a strong foundation in the language, including best practices for testing, debugging, code reuse, and other development tips. This book also shows you how to use Python for applications in business, science, and the arts, using various Python tools and open source packages.
Author: Diego Rodrigues
Publisher: Diego Rodrigues
ISBN:
Category : Computers
Languages : en
Pages : 433
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Book Description
🚀 APROVEITE O VALOR PROMOCIONAL DO LANÇAMENTO DO ANO 🚀 Torne-se um especialista em Python com "40 Bibliotecas Python: Um Guia Essencial para Estudantes e Profissionais - Edição 2024". Este guia de Diego Rodrigues é essencial para estudantes, desenvolvedores e profissionais que desejam dominar Python e suas aplicações práticas. Mergulhe no ecossistema Python explorando bibliotecas poderosas. Use NumPy para computação científica, Pandas para análise de dados, Matplotlib e Seaborn para visualização, Scikit-learn para aprendizado de máquina, TensorFlow e Keras para deep learning. O desenvolvimento web será simples com Flask e Django, enquanto Requests e BeautifulSoup facilitam o web scraping. Aprimore habilidades de visão computacional com OpenCV e Pillow, e desenvolva jogos com PyGame. Descubra SciPy para computação científica e SymPy para matemática simbólica. Use Statsmodels para análise de dados e visualize interativamente com Plotly e Bokeh. Explore NLP com NLTK e spaCy, redes neurais com PyTorch, análise de grafos com NetworkX e mineração de dados com Scrapy. SQLAlchemy otimiza bancos de dados, Celery para processamento paralelo, e PandasQL integra SQL com DataFrames. Manipule grandes dados com Dask, teste software com PyTest e use Jupyter para notebooks interativos. Utilize Hadoop e Spark para Big Data e Kivy e Tkinter para interfaces gráficas. Aplique essas bibliotecas em projetos práticos: análise de grandes volumes de dados, construção de modelos preditivos, desenvolvimento de aplicações web e mobile, automação de tarefas e integração com plataformas como AWS, Google Cloud e Microsoft Azure. Com este livro, adquira habilidades para inovar e liderar no competitivo mundo tecnológico, enfrentando desafios com eficiência. Transforme suas habilidades em uma vantagem estratégica. Este livro prático e focado em resultados acelera seu aprendizado e impulsiona sua carreira. Adquira sua cópia e comece a dominar Python e suas bibliotecas, convertendo desafios em soluções eficazes. Tags: Programação em Python, computação científica, análise de dados, visualização, aprendizado de máquina, inteligência artificial, redes neurais, automação, desenvolvimento web, segurança cibernética, big data, engenharia de software, ciência da computação, análise estatística, mineração de dados, machine learning, deep learning, frameworks web, APIs RESTful, computação em nuvem, inovação tecnológica, eficiência operacional, ciência de dados, visão computacional, processamento de linguagem natural, IoT, segurança em nuvem, DevOps, análise preditiva, Docker, Kubernetes, Hadoop, Spark, SQL, NoSQL, análise de sentimento, testes A/B, modelagem preditiva, design de sistemas, prototipagem, SCRUM, Agile, gestão de projetos, análise de negócios. Python NumPy Pandas Matplotlib Seaborn Scikit-learn TensorFlow Keras Flask Django Requests BeautifulSoup OpenCV Pillow PyGame SciPy SymPy Statsmodels Plotly Bokeh NLTK spaCy PyTorch NetworkX Scrapy SQLAlchemy Celery PandasQL Dask PyTest Jupyter Hadoop Spark Kivy Tkinter automação computação científica visualização de dados inteligência artificial redes neurais machine learning deep learning big data análise de dados ciência da computação engenharia de software segurança cibernética AWS Google Cloud Microsoft Azure APIs RESTful programação Python inovação tecnológica eficiência operacional visão computacional processamento de linguagem natural IoT segurança em nuvem DevOps análise preditiva Docker Kubernetes SQL NoSQL análise de sentimento testes A/B modelagem preditiva design de sistemas prototipagem SCRUM Agile gestão de projetos análise de negócios Diego Rodrigues
