Thousands of readers have learned how to use deep learning's full potential thanks to Deep Learning with Python. Deep learning with Python and Keras is introduced in this thoroughly rewritten second edition, which is fully illustrated and packed with tips for both inexperienced and seasoned machine learning practitioners. You'll pick from useful tips and tricks that you can use immediately as well as crucial theory for developing neural networks.
Python is a multi-paradigm language that makes functional programming simple to use and easy to combine with other programming styles, but it is not a functional programming language. David Mertz, a director of the Python Software Foundation, explores the functional aspects of the language in this paper and identifies which options are generally better to pass on.
This revised edition of Introducing Python is perfect for both novice programmers and readers unfamiliar with the language because it's clear and entertaining to read. In order to illustrate concepts in Python 3, author Bill Lubanovic combines tutorials with code recipes that resemble cookbooks. He progresses from the fundamentals to more complex and diverse themes. Exercises at the end of each chapter allow you to apply what you've learned.
The book will begin with the traditional methods of image processing and discuss the development of image processing algorithms up to the most recent developments in deep learning-based computer vision or image processing. Python image processing libraries like PIL, scikit-mage, and scipy ndimage will be covered in this lesson.
Expose students to various use cases that can be resolved using quantum-based techniques and quickly scale up to quantum computing, quantum machine learning, and associated mathematics. This book explains quantum computing, which makes use of the qubits' quantum mechanical characteristics.
Many Python programmers are interested in machine learning and how it may be used specifically to address problems faced by enterprises that handle moderate to large amounts of data. Machine Learning with Python gives you a detailed, hands-on grasp of the subject while teaching you the fundamentals of machine learning.Important machine learning principles and methods, as well as when and how to employ them, will be covered.
Using Python's greatest capabilities, you'll learn how to build idiomatic, efficient code with this practical book. This book walks you through the essential language features and libraries of Python and demonstrates how to write code that is faster, shorter, and easier to read. This book is excellent for beginners because the lessons cover idiomatic Python and the content is easy to comprehend. This will help developers code stylistically from basic projects to more complex subjects. The book does an excellent job of providing the reader with a strong foundation of information and covering the fundamentals.
Working with Python is a great method to get your programming skills started if you want to learn. Taking you step-by-step through the language, this interactive tutorial starts with fundamental programming ideas and progresses to functions, recursion, data structures, and object-oriented design. The supporting code for this second version has been updated for Python 3. As you learn programming principles, you'll put them to the test with the activities in each chapter. For high school or college students, self-learners, homeschoolers, and professionals who need to learn the fundamentals of programming, Think Python is a great option. Those who are just getting started with Python in a browser will discover where to begin.
The goal of Python for Everyone is to expose students to software development and programming via the lens of data exploration.Consider the Python programming language as your go-to tool for handling data issues that a spreadsheet can't handle. Python is a free programming language that may be used on Linux, Windows, and Mac computers. It is simple to use and quick to learn. Thus, you won't need to buy any software after you learn Python because you can use it for the rest of your career.
Are you looking for a dependable method to study programming independently without getting paralyzed by abstract ideas? The fundamental ideas of computer programming—variables, decisions, loops, functions, and objects—are covered in Head First Programming. These ideas are applicable to all programming languages. This book illustrates and reaffirms these ideas with practical exercises and examples in the lively and flexible Python language. Gain a better knowledge of what software can and cannot do by learning the fundamental tools before beginning to write the applications that interest you. After you're done, you'll have the groundwork needed to take on any software project or master any programming language.
Do you want to learn Python without spending a lot of time poring over how-to guides? Working with the built-in data structures and functions in Head First Python will help you quickly understand the basics of the programming language. After that, you'll develop your own web application and learn about data wrangling, database management, and exception handling. Everything you need to know about using generators, decorators, comprehensions, and context managers can be found here. You may quickly become a proficient Python programmer with the help of this second edition, which offers a comprehensive learning experience.
Among the languages with the fastest growth nowadays is Python. Its varied applications—from web and gaming programming to data analysis and mining to scientific computing, artificial intelligence, and more—as well as its straightforward syntax make it rather simple to learn!...are boosting its renown. Thus, we are at last addressing the need for a Python Murach book. Whether you're a novice programmer or have years of experience, we think it offers the quickest, easiest, and most professional approach to learn Python available.
The journeyman Pythonista can achieve full mastery with the help of The Hitchhiker's Guide to Python. More than any other language, Python was designed with simplicity and parsimony as its primary goals. Python, which is now 25 years old, is now used by many corporate customers as their primary or secondary language, following SQL. Popularity brings diversity and perhaps diluting effects. Written cooperatively by more than a hundred Python community members, this guide outlines the best practices that package and application developers now employ. The Hitchhiker's Guide, in contrast to other publications written for this demographic, focuses more on design philosophy and less on reusable code, pointing the reader toward outstanding pre-existing sources.
This practical book offers a thorough, in-depth introduction to the fundamentals of Python. This revised fifth edition, which is based on author Mark Lutz's well-liked training course, will assist you in writing effective, high-caliber Python code more rapidly. Whether you're an experienced developer with experience in other languages or new to programming, this is a great way to get started. This self-paced, easy-to-follow lesson introduces you to Python 2.7 and 3.3, the most recent versions in the 3.X and 2.X lines, as well as all other releases that are widely used today. It includes quizzes, exercises, and instructive illustrations. Additionally, certain sophisticated language features that are increasingly prevalent in Python programs will be taught to you.
This handy pocket guide, updated for Python 2.7 and 3.4, is an ideal quick reference for on-the-job use. Concise, essential knowledge on Python types and statements, unique method names, built-in functions and exceptions, frequently used standard library modules, and other well-known Python tools may be found here. Using the helpful index, you can quickly identify what you need. Written by Mark Lutz, who is widely acknowledged as the top Python trainer in the world,The Python Pocket Reference is a perfect addition to Mark O'Reilly's well-known Python tutorials, Learning Python and Programming Python.
Learn how to manipulate, analyze, clean, and crunch datasets in Python in detail. The second edition of this practical reference, updated for Python 3.6, is jam-packed with real-world case studies that demonstrate how to efficiently tackle a wide range of data analysis challenges. In the process, you'll learn about the most recent iterations of Jupyter, IPython, NumPy, and pandas. Written by the man behind the Python pandas project, Wes McKinney, this book offers a contemporary, hands-on introduction to Python data science tools. It's perfect for Python programmers who are new to data science and scientific computing, as well as for analysts who are new to Python.
Python has been embraced by the financial sector at a breakneck pace recently; major investment banks and hedge funds are utilizing it to construct key trading and risk management systems. adapted for Python 3. This practical guide, now in its second edition, walks developers and quantitative analysts through the Python libraries and tools needed to create interactive financial analytics and financial apps. Author Yves Hilpisch demonstrates how to create a comprehensive framework for derivatives and risk analytics based on Monte Carlo simulation through the use of real-world examples in the book. The framework is based on a sizable, genuine case study. Interactive I Python notebooks are used extensively in the text.
Unsupervised learning, which may hold the key to general artificial intelligence, is seen by many industry professionals as the next frontier in artificial intelligence. Most of the data in the world is unlabeled, thus traditional supervised learning is not applicable. Conversely, meaningful patterns that may be nearly hard for humans to find in unlabeled datasets can be found through the use of unsupervised learning.
This book provides an extremely approachable introduction to natural language processing, the area of study that underpins many language technologies, such as automatic translation and summarization, email and text prediction, and automatic text filtering. It will teach you how to develop Python programs that handle massive amounts of unstructured text. You will be able to use a wide variety of linguistic data structures to access extensively annotated datasets, and you will be familiar with the primary algorithms for examining the structure and content of written communication.
Python-based machine learning teaches you how to use the two main machine learning algorithms and analyze data properly. This book is able to provide thorough explanations of the mechanisms at work and examples that show the machinery with particular, hackable code because it focuses on two algorithm families that effectively anticipate outcomes. The methods are implemented using Python, with instructions provided on how to choose an algorithm, prepare data, and use the trained models in real-world scenarios. The explanations are straightforward and devoid of complicated arithmetic.
A roadmap for finishing Python projects for programmers who are prepared to advance their abilitiesPython Projects is the best resource for beginning Python programmers who are prepared to go beyond tutorials and begin developing projects.This book, which provides readers with practical, actionable teaching, is the leading resource for bridging the gap between studying and doing. It takes readers through the "where" and "how" of real-world Python programming. Python Projects describes how to utilize Python to accomplish everyday chores and increase productivity for both individuals and enterprises, with an emphasis on practical utility.Python Projects is designed for people who are familiar with the syntax and general usage of Python but may still feel overwhelmed by more intricate, larger projects.
Python is a strong, expressive, and agile programming language that is still gaining popularity. It blends the ease of use and quick creation of scripting languages with the strength of compiled languages. Everything you need to become a versatile Python developer is in this book. In addition to code samples in Python 2 and 3 and migration advice if it's on your roadmap, you will be exposed to a variety of application development topics and acquire information that you can use right away on projects. In fact, several pieces work flawlessly on 2.x or 3.x.
Sams Teach Yourself Python in 24 Hours can help you get started quickly, grasp all the fundamentals of programming, and create anything from games to websites in just 24 one-hour sessions. You'll progress from the very fundamentals to functions, objects, classes, modules, database integration, and more by following this book's simple, step-by-step methodology. Your knowledge base grows with each session and case study application, providing you with a strong basis for success in the real world!
Python Programming and Social Computing A thoroughly modernized and well-researched book, Introduction to Computing and Programming in Python is well known for its effective introduction to the field of media computation. Introduction to Computing and Programming in Python adopts a daring and original approach to computation that engages students and links the subject matter to the relevance of digital media. It places a strong emphasis on creativity, classroom engagement, and in-class programming examples.
The chapters of the book are arranged according to programming themes, such as filesystem usage, text manipulation, and network programming. A chapter's sections each cover one module from the common library. The sections are organized consistently, with a brief introduction outlining the general goal of the module under discussion. The features offered by the module are then explored in a logical sequence, progressing from simple to sophisticated or in the order a programmer would need to use them in an actual application. The code example sections commence with a succinct overview of the example code, succeeded by an explanation and a sample of the program's output.
This course is meant to be used in conjunction with Introduction to Programming Using Python.Daniel Liang is renowned for his "fundamentals-first" method of instructing students on programming ideas and methods. The term "fundamentals-first" refers to the approach where students study basic programming ideas such as functions, loops, and selection statements before developing classes. Prior to learning GUI and object-oriented programming, students study fundamental programming ideas and reasoning. One additional thing about Introduction to Programming Using Python is that, early in the chapter, Liang provides a few examples that employ a simple graphic to get the students interested in programming, in addition to the standard examples that include games and some math.
Using the idea of modularity, Python programming introduces one of the most popular and quickly developing programming languages. The text's thorough explanation of fundamental ideas is one of its strongest points. Many examples of applications from a variety of domains, including database administration, online and mobile application development, are used to illustrate advanced subjects.
Examine every facet of Python programming with this all-inclusive guide. Martin Brown, a seasoned programmer, walks you through the use of complex object-oriented classes starting with the basics of using modules. Key Features: 1 Acquire the skills necessary to design interactive websites, multimedia software, and intricate applications. 2. Although it was developed with the expert coder in mind, even the novice programmer can benefit greatly from this wonderful resource book. 3. Using Python's vast libraries, which include tools for reading and parsing SGML, HTML, and XML files, is also covered in the book.
Python in simple steps shows all the fundamentals of the Python language before presenting instances of CGI scripting and Object-Oriented Programming (OOP) for handling data from web forms. The last section of the book walks you through creating and deploying graphical windowed apps using the skills you have learned. Contents Table: Step One Carrying Out Tasks Declaring Intentions Clarifying Functions Bringing in Modules Programming Objects and Managing Strings Handling Inquiries Constructing Interfaces Creating Apps Index
