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Python: Real World Machine Learning
by Prateek Joshi Luca Massaron John Hearty Bastiaan Sjardin Alberto BoschettiLearn to solve challenging data science problems by building powerful machine learning models using Python About This Book * Understand which algorithms to use in a given context with the help of this exciting recipe-based guide * This practical tutorial tackles real-world computing problems through a rigorous and effective approach * Build state-of-the-art models and develop personalized recommendations to perform machine learning at scale Who This Book Is For This Learning Path is for Python programmers who are looking to use machine learning algorithms to create real-world applications. It is ideal for Python professionals who want to work with large and complex datasets and Python developers and analysts or data scientists who are looking to add to their existing skills by accessing some of the most powerful recent trends in data science. Experience with Python, Jupyter Notebooks, and command-line execution together with a good level of mathematical knowledge to understand the concepts is expected. Machine learning basic knowledge is also expected. What You Will Learn * Use predictive modeling and apply it to real-world problems * Understand how to perform market segmentation using unsupervised learning * Apply your new-found skills to solve real problems, through clearly-explained code for every technique and test * Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms * Increase predictive accuracy with deep learning and scalable data-handling techniques * Work with modern state-of-the-art large-scale machine learning techniques * Learn to use Python code to implement a range of machine learning algorithms and techniques In Detail Machine learning is increasingly spreading in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more. Machine learning is transforming the way we understand and interact with the world around us. In the first module, Python Machine Learning Cookbook, you will learn how to perform various machine learning tasks using a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms. The second module, Advanced Machine Learning with Python, is designed to take you on a guided tour of the most relevant and powerful machine learning techniques and you'll acquire a broad set of powerful skills in the area of feature selection and feature engineering. The third module in this learning path, Large Scale Machine Learning with Python, dives into scalable machine learning and the three forms of scalability. It covers the most effective machine learning techniques on a map reduce framework in Hadoop and Spark in Python. This Learning Path will teach you Python machine learning for the real world. The machine learning techniques covered in this Learning Path are at the forefront of commercial practice. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: * Python Machine Learning Cookbook by Prateek Joshi * Advanced Machine Learning with Python by John Hearty * Large Scale Machine Learning with Python by Bastiaan Sjardin, Alberto Boschetti, Luca Massaron Style and approach This course is a smooth learning path that will teach you how to get started with Python machine learning for the real world, and develop solutions to real-world problems. Through this comprehensive course, you'll learn to create the most effective machine learning techniques from scratch and more!
Python: Master the Art of Design Patterns
by Sakis Kasampalis Dusty Phillips Chetan GiridharEnsure your code is sleek, efficient and elegant by mastering powerful Python design patterns About This Book * Learn all about abstract design patterns and how to implement them in Python 3 * Understand the structural, creational, and behavioral Python design patterns * Get to know the context and application of design patterns to solve real-world problems in software architecture, design, and application development * Discover how to simplify Design Pattern implementation using the power of Python 3 Who This Book Is For If you have basic Python skills and wish to learn in depth how to correctly apply appropriate design patterns, this course is tailor made for you. What You Will Learn * Discover what design patterns are and how to apply them to writing Python * Implement objects in Python by creating classes and defining methods * Separate related objects into a taxonomy of classes and describe the properties and behaviors of those objects via the class interface * Understand when to use object-oriented features, and more importantly when not to use them * Get to know proven solutions to common design issues * Explore the design principles that form the basis of software design, such as loose coupling, the Hollywood principle, and the Open Close principle, among others * Use Structural Design Patterns and find out how objects and classes interact to build larger applications * Improve the productivity and code base of your application using Python design patterns * Secure an interface using the Proxy pattern In Detail Python is an object-oriented scripting language that is used in everything from data science to web development. Known for its simplicity, Python increases productivity and minimizes development time. Through applying essential software engineering design patterns to Python, Python code becomes even more efficient and reusable from project to project. This learning path takes you through every traditional and advanced design pattern best applied to Python code, building your skills in writing exceptional Python. Divided into three distinct modules, you'll go from foundational to advanced concepts by following a series of practical tutorials. Start with the bedrock of Python programming - the object-oriented paradigm. Rethink the way you work with Python as you work through the Python data structures and object-oriented techniques essential to modern Python programming. Build your confidence as you learn Python syntax, and how to use OOP principles with Python tools such as Django and Kivy. In the second module, run through the most common and most useful design patterns from a Python perspective. Progress through Singleton patterns, Factory patterns, Facade patterns and more all with detailed hands-on guidance. Enhance your professional abilities in in software architecture, design, and development. In the final module, run through the more complex and less common design patterns, discovering how to apply them to Python coding with the help of real-world examples. Get to grips with the best practices of writing Python, as well as creating systems architecture and troubleshooting issues. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: * Python 3 Object-Oriented Programming - Second Edition by Dusty Phillips * Learning Python Design Patterns - Second Edition by Chetan Giridhar * Mastering Python Design Patterns by Sakis Kasampalis Style and approach Advance your Python code through three distinct modules that each build on preceding content. Get the complete coverage of Python design patterns you need to write elegant and efficient code that's reusable and powerful.
Python
by James O. KnowltonThis project-based, hands-on book is designed to show you how to use Python to create scripts that are easy to maintain and enhance. Taking a real-world approach, the book explains how Python can be used to solve programming problems. It includes a Python refresher or primer for programmers new to Python. The code provided in the book is simplistic or trivial, but is effective in walking you through the process of creating robust scripts that you can use immediately to create real solutions to the challenges you may face.<P><P> Advisory: Bookshare has learned that this book offers only partial accessibility. We have kept it in the collection because it is useful for some of our members. To explore further access options with us, please contact us through the Book Quality link on the right sidebar. Benetech is actively working on projects to improve accessibility issues such as these.
Python: Penetration Testing for Developers
by Mohit Terry Ip Andrew Mabbitt Cameron Buchanan Dave Mound Benjamin May Christopher DuffyUnleash the power of Python scripting to execute effective and efficient penetration tests About This Book * Sharpen your pentesting skills with Python * Develop your fluency with Python to write sharper scripts for rigorous security testing * Get stuck into some of the most powerful tools in the security world Who This Book Is For If you are a Python programmer or a security researcher who has basic knowledge of Python programming and wants to learn about penetration testing with the help of Python, this course is ideal for you. Even if you are new to the field of ethical hacking, this course can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion. What You Will Learn * Familiarize yourself with the generation of Metasploit resource files and use the Metasploit Remote Procedure Call to automate exploit generation and execution * Exploit the Remote File Inclusion to gain administrative access to systems with Python and other scripting languages * Crack an organization's Internet perimeter and chain exploits to gain deeper access to an organization's resources * Explore wireless traffic with the help of various programs and perform wireless attacks with Python programs * Gather passive information from a website using automated scripts and perform XSS, SQL injection, and parameter tampering attacks * Develop complicated header-based attacks through Python In Detail Cybercriminals are always one step ahead, when it comes to tools and techniques. This means you need to use the same tools and adopt the same mindset to properly secure your software. This course shows you how to do just that, demonstrating how effective Python can be for powerful pentesting that keeps your software safe. Comprising of three key modules, follow each one to push your Python and security skills to the next level. In the first module, we'll show you how to get to grips with the fundamentals. This means you'll quickly find out how to tackle some of the common challenges facing pentesters using custom Python tools designed specifically for your needs. You'll also learn what tools to use and when, giving you complete confidence when deploying your pentester tools to combat any potential threat. In the next module you'll begin hacking into the application layer. Covering everything from parameter tampering, DDoS, XXS and SQL injection, it will build on the knowledge and skills you learned in the first module to make you an even more fluent security expert. Finally in the third module, you'll find more than 60 Python pentesting recipes. We think this will soon become your trusted resource for any pentesting situation. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: * Learning Penetration Testing with Python by Christopher Duffy * Python Penetration Testing Essentials by Mohit * Python Web Penetration Testing Cookbook by Cameron Buchanan,Terry Ip, Andrew Mabbitt, Benjamin May and Dave Mound Style and approach This course provides a quick access to powerful, modern tools, and customizable scripts to kick-start the creation of your own Python web penetration testing toolbox.
Python: Master the Art of Design Patterns
by Dusty Phillips Chetan Giridhar Sakis KasampalisEnsure your code is sleek, efficient and elegant by mastering powerful Python design patterns About This Book Learn all about abstract design patterns and how to implement them in Python 3 Understand the structural, creational, and behavioral Python design patterns Get to know the context and application of design patterns to solve real-world problems in software architecture, design, and application development Discover how to simplify Design Pattern implementation using the power of Python 3 Who This Book Is For If you have basic Python skills and wish to learn in depth how to correctly apply appropriate design patterns, this course is tailor made for you. What You Will Learn Discover what design patterns are and how to apply them to writing Python Implement objects in Python by creating classes and defining methods Separate related objects into a taxonomy of classes and describe the properties and behaviors of those objects via the class interface Understand when to use object-oriented features, and more importantly when not to use them Get to know proven solutions to common design issues Explore the design principles that form the basis of software design, such as loose coupling, the Hollywood principle, and the Open Close principle, among others Use Structural Design Patterns and find out how objects and classes interact to build larger applications Improve the productivity and code base of your application using Python design patterns Secure an interface using the Proxy pattern In Detail Python is an object-oriented scripting language that is used in everything from data science to web development. Known for its simplicity, Python increases productivity and minimizes development time. Through applying essential software engineering design patterns to Python, Python code becomes even more efficient and reusable from project to project. This learning path takes you through every traditional and advanced design pattern best applied to Python code, building your skills in writing exceptional Python. Divided into three distinct modules, you'll go from foundational to advanced concepts by following a series of practical tutorials. Start with the bedrock of Python programming – the object-oriented paradigm. Rethink the way you work with Python as you work through the Python data structures and object-oriented techniques essential to modern Python programming. Build your confidence as you learn Python syntax, and how to use OOP principles with Python tools such as Django and Kivy. In the second module, run through the most common and most useful design patterns from a Python perspective. Progress through Singleton patterns, Factory patterns, Facade patterns and more all with detailed hands-on guidance. Enhance your professional abilities in in software architecture, design, and development. In the final module, run through the more complex and less common design patterns, discovering how to apply them to Python coding with the help of real-world examples. Get to grips with the best practices of writing Python, as well as creating systems architecture and troubleshooting issues. This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: Python 3 Object-Oriented Programming - Second Edition by Dusty Phillips Learning Python Design Patterns - Second Edition by Chetan Giridhar Mastering Python Design Patterns by Sakis Kasampalis Style and approach Advance your Python code through three distinct modules that each build on preceding content. Get the complete coverage of Python design patterns you need to write elegant and efficient code that's reusable and powerful.
Python: Real-World Data Science
by Dusty Phillips Fabrizio Romano Martin Czygan Phuong Vo.T.H Robert Layton Sebastian RaschkaUnleash the power of Python and its robust data science capabilities About This Book • Unleash the power of Python 3 objects • Learn to use powerful Python libraries for effective data processing and analysis • Harness the power of Python to analyze data and create insightful predictive models • Unlock deeper insights into machine learning with this vital guide to cutting-edge predictive analytics Who This Book Is For Entry-level analysts who want to enter in the data science world will find this course very useful to get themselves acquainted with Python's data science capabilities for doing real-world data analysis. What You Will Learn • Install and setup Python • Implement objects in Python by creating classes and defining methods • Get acquainted with NumPy to use it with arrays and array-oriented computing in data analysis • Create effective visualizations for presenting your data using Matplotlib • Process and analyze data using the time series capabilities of pandas • Interact with different kind of database systems, such as file, disk format, Mongo, and Redis • Apply data mining concepts to real-world problems • Compute on big data, including real-time data from the Internet • Explore how to use different machine learning models to ask different questions of your data In Detail The Python: Real-World Data Science course will take you on a journey to become an efficient data science practitioner by thoroughly understanding the key concepts of Python. This learning path is divided into four modules and each module are a mini course in their own right, and as you complete each one, you'll have gained key skills and be ready for the material in the next module. The course begins with getting your Python fundamentals nailed down. After getting familiar with Python core concepts, it's time that you dive into the field of data science. In the second module, you'll learn how to perform data analysis using Python in a practical and example-driven way. The third module will teach you how to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis to more complex data types including text, images, and graphs. Machine learning and predictive analytics have become the most important approaches to uncover data gold mines. In the final module, we'll discuss the necessary details regarding machine learning concepts, offering intuitive yet informative explanations on how machine learning algorithms work, how to use them, and most importantly, how to avoid the common pitfalls. Style and approach This course includes all the resources that will help you jump into the data science field with Python and learn how to make sense of data. The aim is to create a smooth learning path that will teach you how to get started with powerful Python libraries and perform various data science techniques in depth.
Python: Data Analytics and Visualization
by Phuong Vo.T.H Martin Czygan Kirthi Raman Ashish KumarUnderstand, evaluate, and visualize data About This Book • Learn basic steps of data analysis and how to use Python and its packages • A step-by-step guide to predictive modeling including tips, tricks, and best practices • Effectively visualize a broad set of analyzed data and generate effective results Who This Book Is For This book is for Python Developers who are keen to get into data analysis and wish to visualize their analyzed data in a more efficient and insightful manner. What You Will Learn • Get acquainted with NumPy and use arrays and array-oriented computing in data analysis • Process and analyze data using the time-series capabilities of Pandas • Understand the statistical and mathematical concepts behind predictive analytics algorithms • Data visualization with Matplotlib • Interactive plotting with NumPy, Scipy, and MKL functions • Build financial models using Monte-Carlo simulations • Create directed graphs and multi-graphs • Advanced visualization with D3 In Detail You will start the course with an introduction to the principles of data analysis and supported libraries, along with NumPy basics for statistics and data processing. Next, you will overview the Pandas package and use its powerful features to solve data-processing problems. Moving on, you will get a brief overview of the Matplotlib API .Next, you will learn to manipulate time and data structures, and load and store data in a file or database using Python packages. You will learn how to apply powerful packages in Python to process raw data into pure and helpful data using examples. You will also get a brief overview of machine learning algorithms, that is, applying data analysis results to make decisions or building helpful products such as recommendations and predictions using Scikit-learn. After this, you will move on to a data analytics specialization—predictive analytics. Social media and IOT have resulted in an avalanche of data. You will get started with predictive analytics using Python. You will see how to create predictive models from data. You will get balanced information on statistical and mathematical concepts, and implement them in Python using libraries such as Pandas, scikit-learn, and NumPy. You'll learn more about the best predictive modeling algorithms such as Linear Regression, Decision Tree, and Logistic Regression. Finally, you will master best practices in predictive modeling. After this, you will get all the practical guidance you need to help you on the journey to effective data visualization. Starting with a chapter on data frameworks, which explains the transformation of data into information and eventually knowledge, this path subsequently cover the complete visualization process using the most popular Python libraries with working examples This Learning Path combines some of the best that Packt has to offer in one complete, curated package. It includes content from the following Packt products: ? Getting Started with Python Data Analysis, Phuong Vo.T.H &Martin Czygan ? Learning Predictive Analytics with Python, Ashish Kumar ? Mastering Python Data Visualization, Kirthi Raman Style and approach The course acts as a step-by-step guide to get you familiar with data analysis and the libraries supported by Python with the help of real-world examples and datasets. It also helps you gain practical insights into predictive modeling by implementing predictive-analytics algorithms on public datasets with Python. The course offers a wealth of practical guidance to help you on this journey to data visualization
Python: A Practical Learning Approach
by Shriram K. Vasudevan Sini Raj Pulari T.S. MurugeshPython’s simplicity and versatility make it an ideal language for both beginners and experienced programmers. Its syntax facilitates a smooth learning curve, enabling individuals to concentrate on grasping programming concepts instead of wrestling with intricate syntax rules. The extensive standard library reinforces its practicality, offering pre-built modules and functions that reduce manual coding efforts. Python’s versatility is evident in its applications, spanning web development, data analysis, Machine Learning and automation.The language’s interactive nature supports real-time code experimentation, stepping up the learning process and enhancing understanding. Python’s wealth of online resources further enriches the learning experience, fostering a community where individuals can develop their programming skills. Python: A Practical Learning Approach exemplifies Python’s simplicity and versatility with numerous examples, ensuring a seamless learning journey. Beyond theory, the language’s practicality allows learners to actively apply their knowledge in real-world scenarios, establishing Python as an asset in education.
Python: La Guía Definitiva para Principiantes para Dominar Python
by Jonathan S. Walker Angel MartinezDomina El Lenguaje de Programación PYTHON En Esta Guía Definitiva Para Principiantes HoyMismo! Estás buscando un modo de utilizar la programación en Python con eficacia? ¿Quieres aprender a programar rápidamente y sin esfuerzo? Te presentamos La Guía Definitiva Para Principiantes Para El Dominiar Python. Los lenguajes de prrogramación son fascinantes y asustan al mismo tiempo porque pueden ayudarnos a progresar en nuestras vidas, pero a la vez, tendremos que aprender a escribir código utilizando funciones que puede que no comprendamos en este momento,En Este Libro Aprenderás·
Python 2.6 Graphics Cookbook
by Mike Ohlson FineThis book has recipes that show enthusiastic users how easy graphic programming can be. Simple explanations in plain English are used. The recipes are built up, in each chapter, starting as simply as possible and moving to more complex programs with which you can comfortably create 2D vector graphics and animations. You will learn how to combine both vector and photo images seamlessly! If you are looking to create animated graphics to represent real-world scenarios then this book is for you. Teachers, scholars, students, and engineers who know it is possible to make fascinating models and demonstrations but have not found a handbook that pulls it all together in one place will find what they need in this recipe bank. Basic knowledge of Python programming is required and access to the Web and Google will be useful.
Python 2.6 Text Processing: Beginners Guide
by Jeff McneilThis book is part of the Beginner's Guide series. Each chapter covers the steps for various tasks to process data followed by brief explanation of what is happening in each task. The explanation is followed by a few questions on the topic under discussion that will serve as a refresher course for you. This book is for people who have text in one format, and need it in another, as quickly as possible. You don't need any experience with text processing, but you will need some basic knowledge of Python.
Python 3 - Intensivkurs
by Mark Pilgrim Florian WollenscheinPython ist eine vollwertige Programmiersprache, mit der sich auch größere Anwendungen entwickeln lassen. In den letzten Jahren hat sie an Beliebtheit gewonnen, und mit Python 3 steht eine stark erweiterte Version zur Verfügung. In dem Band werden die Werkzeuge und Programmiermöglichkeiten praxisorientiert vorgestellt. Jedes Kapitel beginnt mit einem vollwertigen, lauffähigen Codebeispiel, das jeweils ausführlich analysiert wird. Im Vordergrund stehen die unmittelbare praktische Anwendung und die Realisierung von Projekten mit Python 3.
Python 3 Object Oriented Programming
by Dusty PhillipsThe book begins with the very foundations of OOP and then uses practical examples to show how to correctly implement Object Oriented Programming in Python. Many examples are taken from real-world projects. The book focuses on high-level design as well as the gritty details of the Python syntax. The provided exercises inspire the reader to think about his or her own code, rather than providing solved problems. If you're new to Object Oriented Programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply Object Oriented Programming in Python, this is the book for you. If you are an object-oriented programmer for other languages, you too will find this book a useful introduction to Python, as it uses terminology you are already familiar with. Python 2 programmers seeking a leg up in the new world of Python 3 will also find the book beneficial, and you need not necessarily know Python 2.
Python 3 Object-Oriented Programming: Build robust and maintainable software with object-oriented design patterns in Python 3.8, 3rd Edition
by Dusty PhillipsUncover modern Python with this guide to Python data structures, design patterns, and effective object-oriented techniquesKey FeaturesIn-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique styleLearn the latest Python syntax and librariesExplore abstract design patterns and implement them in Python 3.8Book DescriptionObject-oriented programming (OOP) is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. This third edition of Python 3 Object-Oriented Programming fully explains classes, data encapsulation, and exceptions with an emphasis on when you can use each principle to develop well-designed software. Starting with a detailed analysis of object-oriented programming, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. You will learn how to create maintainable applications by studying higher level design patterns. The book will show you the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems, unittest and pytest, will be introduced in this book. You'll get a comprehensive introduction to Python's concurrent programming ecosystem. By the end of the book, you will have thoroughly learned object-oriented principles using Python syntax and be able to create robust and reliable programs confidently.What you will learnImplement objects in Python by creating classes and defining methodsGrasp common concurrency techniques and pitfalls in Python 3Extend class functionality using inheritanceUnderstand when to use object-oriented features, and more importantly when not to use themDiscover what design patterns are and why they are different in PythonUncover the simplicity of unit testing and why it's so important in PythonExplore concurrent object-oriented programmingWho this book is forIf you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply OOP in Python, this is the book for you. If you are an object-oriented programmer for other languages or seeking a leg up in the new world of Python 3.8, you too will find this book a useful introduction to Python. Previous experience with Python 3 is not necessary.
Python 3 Object-oriented Programming - Second Edition
by Dusty PhillipsUnleash the power of Python 3 objects About This Book Stop writing scripts and start architecting programs Learn the latest Python syntax and libraries A practical, hands-on tutorial that teaches you all about abstract design patterns and how to implement them in Python 3 Who This Book Is For If you're new to object-oriented programming techniques, or if you have basic Python skills and wish to learn in depth how and when to correctly apply object-oriented programming in Python to design software, this is the book for you. What You Will Learn Implement objects in Python by creating classes and defining methods Separate related objects into a taxonomy of classes and describe the properties and behaviors of those objects via the class interface Extend class functionality using inheritance Understand when to use object-oriented features, and more importantly when not to use them Discover what design patterns are and why they are different in Python Uncover the simplicity of unit testing and why it's so important in Python Grasp common concurrency techniques and pitfalls in Python 3 Exploit object-oriented programming in key Python technologies such as Kivy and Django. Object-oriented programming concurrently with asyncio In Detail Python 3 is more versatile and easier to use than ever. It runs on all major platforms in a huge array of use cases. Coding in Python minimizes development time and increases productivity in comparison to other languages. Clean, maintainable code is easy to both read and write using Python's clear, concise syntax. Object-oriented programming is a popular design paradigm in which data and behaviors are encapsulated in such a way that they can be manipulated together. Many modern programming languages utilize the powerful concepts behind object-oriented programming and Python is no exception. Starting with a detailed analysis of object-oriented analysis and design, you will use the Python programming language to clearly grasp key concepts from the object-oriented paradigm. This book fully explains classes, data encapsulation, inheritance, polymorphism, abstraction, and exceptions with an emphasis on when you can use each principle to develop well-designed software. You'll get an in-depth analysis of many common object-oriented design patterns that are more suitable to Python's unique style. This book will not just teach Python syntax, but will also build your confidence in how to program. You will also learn how to create maintainable applications by studying higher level design patterns. Following this, you'll learn the complexities of string and file manipulation, and how Python distinguishes between binary and textual data. Not one, but two very powerful automated testing systems will be introduced in the book. After you discover the joy of unit testing and just how easy it can be, you'll study higher level libraries such as database connectors and GUI toolkits and learn how they uniquely apply object-oriented principles. You'll learn how these principles will allow you to make greater use of key members of the Python eco-system such as Django and Kivy. This new edition includes all the topics that made Python 3 Object-oriented Programming an instant Packt classic. It's also packed with updated content to reflect recent changes in the core Python library and covers modern third-party packages that were not available on the Python 3 platform when the book was first published. Style and approach Throughout the book you will learn key object-oriented programming techniques demonstrated by comprehensive case studies in the context of a larger project.
Python 3 Text Processing with NLTK 3 Cookbook
by Jacob PerkinsThis book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basic text processing concepts is expected. Some experience with regular expressions will also be helpful.
Python 3 Web Development Beginner's Guide
by Michel AndersPart of Packt's Beginner's Guide Series, this book follows a sample application, with lots of screenshots, to help you get to grips with the techniques as quickly as possible. Moderately experienced Python programmers who want to learn how to create fairly complex, database-driven, cross browser compatible web apps that are maintainable and look good will find this book of most use. All key technologies except for Python 3 are explained in detail.
Python Adventures for Young Coders: Explore the World of Programming
by Alaa TharwatThis book takes young readers on an exciting adventure with a child named Kai. One day, Kai wakes up trapped inside a giant robot. He can't talk to anyone outside, and the only way to communicate is through the robot. Inside the robot, Kai finds many books and documents written in a strange language—it's the robot's language, which is Python. Kai realizes he needs to learn this language to control the robot and talk to the outside world. In each chapter in this book, we will join Kai on a new adventure to learn something that helps us control the robot better and communicate with the real world. This fun and interactive book is designed to introduce young minds to the basics of programming while encouraging creativity and problem-solving skills. In the introductory chapters, readers discover Python as a friendly and accessible programming language. The book guides them through setting up their programming environment and crafting their initial lines of code, laying the foundation for an exciting coding adventure. As the exploration unfolds, it delves into fundamental programming concepts essential for any budding coder. From variables and data types to loops and conditionals, these building blocks empower readers to create their programs, fostering a solid understanding of the core principles of coding. It seamlessly integrates these concepts with previously learned fundamentals, providing a comprehensive view of Python's capabilities. Fueling creativity, it inspires readers to unleash their imagination through engaging projects. From crafting games to developing useful applications, young coders learn to apply their programming skills in innovative ways, transforming abstract coding concepts into real and interactive projects. With a focus on accessibility, engagement, and real-world application, this book paves the way for the next generation of Python enthusiasts. What you will learn: Understand Python programming fundamentals, including syntax, variables, data types, loops, conditionals, lists, functions, and handling files. Learn to break down complex problems into smaller, manageable tasks and apply coding concepts to find creative solutions. How to create their interactive coding projects using Python. Understand strategies for debugging and troubleshooting common programming problems, which are essential skills for any programmer Who this book is for: This book caters primarily for high school students and individuals keen on delving into programming with minimal or zero coding background. It's structured to be both accessible and captivating for young readers, immersing them in the realm of coding through entertaining and interactive journeys. Moreover, it extends its reach to educators and coding enthusiasts alike.
Python Algorithmic Trading Cookbook: All The Recipes You Need To Implement Your Own Trading Strategies In Python
by Pushpak DagadeIf you are a financial analyst, financial trader, data analyst, or algorithmic trader who wants to learn algorithmic trading techniques to address challenges faced in the finance domain, then this book is for you. Basic knowledge of financial terminologies and working knowledge of the Python programming language are expected.
Python Algorithms
by Magnus Lie HetlandPython Algorithms, Second Edition explains the Python approach to algorithm analysis and design. Written by Magnus Lie Hetland, author of Beginning Python, this book is sharply focused on classical algorithms, but it also gives a solid understanding of fundamental algorithmic problem-solving techniques. The book deals with some of the most important and challenging areas of programming and computer science in a highly readable manner. It covers both algorithmic theory and programming practice, demonstrating how theory is reflected in real Python programs. Well-known algorithms and data structures that are built into the Python language are explained, and the user is shown how to implement and evaluate others.
Python All-in-One For Dummies
by John C. Shovic Alan SimpsonEverything you need to know to get into Python coding, with 7 books in one Python All-in-One For Dummies is your one-stop source for answers to all your Python questions. From creating apps to building complex web sites to sorting big data, Python provides a way to get the work done. This book is great as a starting point for those new to coding, and it also makes a perfect reference for experienced coders looking for more than the basics. Apply your Python skills to data analysis, learn to write AI-assisted code using GitHub CoPilot, and discover many more exciting uses for this top programming language. Get started coding in Python—even if you’re new to computer programming Reference all the essentials and the latest updates, so your code is air-tight Learn how Python can be a solution for large-scale projects and big datasets Accelerate your career path with this comprehensive guide to learning PythonExperienced and would-be coders alike will love this easy-to-follow guide to learning and applying Python.
Python All-in-One For Dummies
by John C. Shovic Alan SimpsonThe one-stop resource for all your Python queries Powerful and flexible, Python is one of the most popular programming languages in the world. It’s got all the right stuff for the software driving the cutting-edge of the development world—machine learning, robotics, artificial intelligence, data science, etc. The good news is that it’s also pretty straightforward to learn, with a simplified syntax, natural-language flow, and an amazingly supportive user community. The latest edition of Python All-in-One For Dummies gives you an inside look at the exciting possibilities offered in the Python world and provides a springboard to launch yourself into wherever you want your coding career to take you. These 7 straightforward and friendly mini-books assume the reader is a beginning programmer, and cover everything from the basic elements of Python code to introductions to the specific applications where you’ll use it. Intended as a hands-on reference, the focus is on practice over theory, providing you with examples to follow as well as code for you to copy and start modifying in the “real world”—helping you get up and running in your area of interest almost right away. This means you’ll be finishing off your first app or building and remote-controlling your own robot much faster than you can believe. Get a thorough grounding in the language basics Learn how the syntax is applied in high-profile industries Apply Python to projects in enterprise Find out how Python can get you into hot careers in AI, big data, and more Whether you’re a newbie coder or just want to add Python to your magic box of tricks, this is the perfect, practical introduction—and one you’ll return to as you grow your career.
Python All-in-One For Dummies
by Alan Simpson John ShovicYour one-stop resource on all things Python Thanks to its flexibility, Python has grown to become one of the most popular programming languages in the world. Developers use Python in app development, web development, data science, machine learning, and even in coding education classes. There's almost no type of project that Python can't make better. From creating apps to building complex websites to sorting big data, Python provides a way to get the work done. Python All-in-One For Dummies offers a starting point for those new to coding by explaining the basics of Python and demonstrating how it’s used in a variety of applications. Covers the basics of the language Explains its syntax through application in high-profile industries Shows how Python can be applied to projects in enterprise Delves into major undertakings including artificial intelligence, physical computing, machine learning, robotics and data analysis This book is perfect for anyone new to coding as well as experienced coders interested in adding Python to their toolbox.
Python and AWS Cookbook
by Mitch GarnaatIf you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. You'll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services. This book's recipes include methods to help you: Launch instances on EC2, and keep track of them with tags Associate an Elastic IP address with an instance Restore a failed Elastic Block Store volume from a snapshot Store and monitor your own custom metrics in CloudWatch Create a bucket in S3 to contain your data objects Reduce the cost of storing noncritical data Prevent accidental deletion of data in S3
Python and AWS Cookbook: Managing Your Cloud with Python and Boto
by Mitch GarnaatIf you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author’s boto library.You’ll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services.This book’s recipes include methods to help you:Launch instances on EC2, and keep track of them with tagsAssociate an Elastic IP address with an instanceRestore a failed Elastic Block Store volume from a snapshotStore and monitor your own custom metrics in CloudWatchCreate a bucket in S3 to contain your data objectsReduce the cost of storing noncritical dataPrevent accidental deletion of data in S3