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Author : Vernon L. Ceder,Naomi R. Ceder
Publisher : Manning Publications Company
Page : 336 pages
File Size : 47,5 Mb
Release : 2010
Category : Computers
ISBN : 193518220X
Introduces the programming language's syntax, control flow, and basic data structures and covers its interaction with applications and mangement of large collections of code.
Author : Chris Conlan
Publisher : Unknown
Page : 152 pages
File Size : 49,9 Mb
Release : 2020-05-31
Category : Electronic
ISBN : 9798646722080
Fast Python aggressively rehashes the basics of Python programming in order to dispel myths and misconceptions about how to write fast code. Readers equipped with the lessons from this book will be able to test, diagnose, and optimize out performance bottlenecks in their own work. For each algorithm discussed, readers will walk through numerous progressively faster methods of programming it, all while picking up bits of fundamental knowledge about time complexity, memory efficiency, data structures, multi-threading, and vectorization. As such, this book is relevant to veterans looking refresh their methods and to computer science students navigating Algorithms 101. This book maintains a high standard of reproducibility. All of the graphics, tables, and code profiles contained in this book are fully reproducible and available to anyone in a public GitHub repository.
Author : Tiago Antao
Publisher : Simon and Schuster
Page : 302 pages
File Size : 46,7 Mb
Release : 2023-05-30
Category : Computers
ISBN : 9781617297939
Master these effective techniques to reduce costs and run times, handle huge datasets, and implement complex machine learning applications efficiently in Python. Fast Python is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Author : Jason Scotts
Publisher : Speedy Publishing LLC
Page : 40 pages
File Size : 44,8 Mb
Release : 2013-11-02
Category : Computers
ISBN : 9781630222468
Are you fed up with reading long, boring, lengthy paragraphs after paragraphs of text and want to get up and running in Python as soon as possible? Well, you're not alone. I for one hate having to read through masses of text for very little benefit. Python Programming Reloaded: How to Code Python Fast In Just 24 Hours With 7 Simple Steps strips away the non essentials and instead provides you with the fundamentals from which you can blossom as a Python programmer in Just 7 simple steps. So, what can I expect from the book? Learn the Basics- this book provides you with the fundamental building blocks to get you up and running in Python in no time. Learn it Quick -Written for simplicity so that you can learn Python quickly and efficiently. Start Coding Fast -You start coding as soon as Python is installed on your computer. Anything else? Yes!. This book will supercharge your Python learning experience.
Author : Jeremy Howard,Sylvain Gugger
Publisher : O'Reilly Media
Page : 624 pages
File Size : 40,5 Mb
Release : 2020-06-29
Category : Computers
ISBN : 9781492045496
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Author : Micha Gorelick,Ian Ozsvald
Publisher : O'Reilly Media
Page : 469 pages
File Size : 50,7 Mb
Release : 2020-04-30
Category : Computers
ISBN : 9781492054993
Your Python code may run correctly, but you need it to run faster. Updated for Python 3, this expanded edition shows you how to locate performance bottlenecks and significantly speed up your code in high-data-volume programs. By exploring the fundamental theory behind design choices, High Performance Python helps you gain a deeper understanding of Python’s implementation. How do you take advantage of multicore architectures or clusters? Or build a system that scales up and down without losing reliability? Experienced Python programmers will learn concrete solutions to many issues, along with war stories from companies that use high-performance Python for social media analytics, productionized machine learning, and more. Get a better grasp of NumPy, Cython, and profilers Learn how Python abstracts the underlying computer architecture Use profiling to find bottlenecks in CPU time and memory usage Write efficient programs by choosing appropriate data structures Speed up matrix and vector computations Use tools to compile Python down to machine code Manage multiple I/O and computational operations concurrently Convert multiprocessing code to run on local or remote clusters Deploy code faster using tools like Docker
Author : Tiago Antao
Publisher : Simon and Schuster
Page : 302 pages
File Size : 54,8 Mb
Release : 2023-07-04
Category : Computers
ISBN : 9781638356868
Master Python techniques and libraries to reduce run times, efficiently handle huge datasets, and optimize execution for complex machine learning applications. Fast Python is a toolbox of techniques for high performance Python including: Writing efficient pure-Python code Optimizing the NumPy and pandas libraries Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing Fast Python is your guide to optimizing every part of your Python-based data analysis process, from the pure Python code you write to managing the resources of modern hardware and GPUs. You'll learn to rewrite inefficient data structures, improve underperforming code with multithreading, and simplify your datasets without sacrificing accuracy. Written for experienced practitioners, this book dives right into practical solutions for improving computation and storage efficiency. You'll experiment with fun and interesting examples such as rewriting games in Cython and implementing a MapReduce framework from scratch. Finally, you'll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the Technology Face it. Slow code will kill a big data project. Fast pure-Python code, optimized libraries, and fully utilized multiprocessor hardware are the price of entry for machine learning and large-scale data analysis. What you need are reliable solutions that respond faster to computing requirements while using less resources, and saving money. About the Book Fast Python is a toolbox of techniques for speeding up Python, with an emphasis on big data applications. Following the clear examples and precisely articulated details, you’ll learn how to use common libraries like NumPy and pandas in more performant ways and transform data for efficient storage and I/O. More importantly, Fast Python takes a holistic approach to performance, so you’ll see how to optimize the whole system, from code to architecture. What’s Inside Rewriting critical code in Cython Designing persistent data structures Tailoring code for different architectures Implementing Python GPU computing About the Reader For intermediate Python programmers familiar with the basics of concurrency. About the Author Tiago Antão is one of the co-authors of Biopython, a major bioinformatics package written in Python. Table of Contents: PART 1 - FOUNDATIONAL APPROACHES 1 An urgent need for efficiency in data processing 2 Extracting maximum performance from built-in features 3 Concurrency, parallelism, and asynchronous processing 4 High-performance NumPy PART 2 - HARDWARE 5 Re-implementing critical code with Cython 6 Memory hierarchy, storage, and networking PART 3 - APPLICATIONS AND LIBRARIES FOR MODERN DATA PROCESSING 7 High-performance pandas and Apache Arrow 8 Storing big data PART 4 - ADVANCED TOPICS 9 Data analysis using GPU computing 10 Analyzing big data with Dask
Author : Naomi Ceder
Publisher : Simon and Schuster
Page : 668 pages
File Size : 43,5 Mb
Release : 2018-05-03
Category : Computers
ISBN : 9781638353430
Summary This third revision of Manning's popular The Quick Python Book offers a clear, crisp updated introduction to the elegant Python programming language and its famously easy-to-read syntax. Written for programmers new to Python, this latest edition includes new exercises throughout. It covers features common to other languages concisely, while introducing Python's comprehensive standard functions library and unique features in detail. Foreword by Nicholas Tollervey, Python Software Foundation. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Initially Guido van Rossum's 1989 holiday project, Python has grown into an amazing computer language. It's a joy to learn and read, and powerful enough to handle everything from low-level system resources to advanced applications like deep learning. Elegantly simple and complete, it also boasts a massive ecosystem of libraries and frameworks. Python programmers are in high demand/mdash;you can't afford not to be fluent! About the Book The Quick Python Book, Third Edition is a comprehensive guide to the Python language by a Python authority, Naomi Ceder. With the personal touch of a skilled teacher, she beautifully balances details of the language with the insights and advice you need to handle any task. Extensive, relevant examples and learn-by-doing exercises help you master each important concept the first time through. Whether you're scraping websites or playing around with nested tuples, you'll appreciate this book's clarity, focus, and attention to detail. What's Inside Clear coverage of Python 3 Core libraries, packages, and tools In-depth exercises Five new data science-related chapters About the Reader Written for readers familiar with programming concepts--no Python experience assumed. About the Author Naomi Ceder is chair of the Python Software Foundation. She has been learning, using, and teaching Python since 2001. Table of Contents PART 1 - STARTING OUT 1. About Python 2. Getting started 3. The Quick Python overview PART 2 - THE ESSENTIALS 4. The absolute basics 5. Lists, tuples, and sets 6. Strings 7. Dictionaries 8. Control flow 9. Functions 10. Modules and scoping rules 11. Python programs 12. Using the filesystem 13. Reading and writing files 14. Exceptions PART 3 - ADVANCED LANGUAGE FEATURES 15. Classes and object-oriented programming 16. Regular expressions 17. Data types as objects 18. Packages 19. Using Python libraries PART 4 - WORKING WITH DATA 20. Basic file wrangling 21. Processing data files 22. Data over the network 23. Saving data 24. Exploring data
Author : Jamie Chan
Publisher : Createspace Independent Publishing Platform
Page : 174 pages
File Size : 54,9 Mb
Release : 2017-05-04
Category : Computer programming
ISBN : 1546488332
"Have you always wanted to learn computer programming but are afraid it'll be too difficult for you? Or perhaps you know other programming languages but are interested in learning the Python language fast? This book is for you"--Page 4 of cover.
Author : Eric Matthes
Publisher : No Starch Press
Page : 564 pages
File Size : 53,7 Mb
Release : 2015-11-01
Category : Computers
ISBN : 9781593277390
Python Crash Course is a fast-paced, thorough introduction to Python that will have you writing programs, solving problems, and making things that work in no time. In the first half of the book, you’ll learn about basic programming concepts, such as lists, dictionaries, classes, and loops, and practice writing clean and readable code with exercises for each topic. You’ll also learn how to make your programs interactive and how to test your code safely before adding it to a project. In the second half of the book, you’ll put your new knowledge into practice with three substantial projects: a Space Invaders–inspired arcade game, data visualizations with Python’s super-handy libraries, and a simple web app you can deploy online. As you work through Python Crash Course you’ll learn how to: –Use powerful Python libraries and tools, including matplotlib, NumPy, and Pygal –Make 2D games that respond to keypresses and mouse clicks, and that grow more difficult as the game progresses –Work with data to generate interactive visualizations –Create and customize Web apps and deploy them safely online –Deal with mistakes and errors so you can solve your own programming problems If you’ve been thinking seriously about digging into programming, Python Crash Course will get you up to speed and have you writing real programs fast. Why wait any longer? Start your engines and code! Uses Python 2 and 3
Author : Gregory Walters
Publisher : Apress
Page : 140 pages
File Size : 45,7 Mb
Release : 2014-02-28
Category : Computers
ISBN : 9781430264798
The Python Quick Syntax Reference is the "go to" book that contains an easy to read and use guide to Python programming and development. This condensed code and syntax reference presents the Python language in a well-organized format designed to be used time and again. You won't find jargon, bloated samples, case studies, or history of Hello World and computer theory in this handy reference. This Python syntax reference is packed with useful information and is a must-have for any Python developer.
Author : Boris Paskhaver
Publisher : Simon and Schuster
Page : 438 pages
File Size : 54,7 Mb
Release : 2021-10-12
Category : Computers
ISBN : 9781638351047
Take the next steps in your data science career! This friendly and hands-on guide shows you how to start mastering Pandas with skills you already know from spreadsheet software. In Pandas in Action you will learn how to: Import datasets, identify issues with their data structures, and optimize them for efficiency Sort, filter, pivot, and draw conclusions from a dataset and its subsets Identify trends from text-based and time-based data Organize, group, merge, and join separate datasets Use a GroupBy object to store multiple DataFrames Pandas has rapidly become one of Python's most popular data analysis libraries. In Pandas in Action, a friendly and example-rich introduction, author Boris Paskhaver shows you how to master this versatile tool and take the next steps in your data science career. You’ll learn how easy Pandas makes it to efficiently sort, analyze, filter and munge almost any type of data. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Data analysis with Python doesn’t have to be hard. If you can use a spreadsheet, you can learn pandas! While its grid-style layouts may remind you of Excel, pandas is far more flexible and powerful. This Python library quickly performs operations on millions of rows, and it interfaces easily with other tools in the Python data ecosystem. It’s a perfect way to up your data game. About the book Pandas in Action introduces Python-based data analysis using the amazing pandas library. You’ll learn to automate repetitive operations and gain deeper insights into your data that would be impractical—or impossible—in Excel. Each chapter is a self-contained tutorial. Realistic downloadable datasets help you learn from the kind of messy data you’ll find in the real world. What's inside Organize, group, merge, split, and join datasets Find trends in text-based and time-based data Sort, filter, pivot, optimize, and draw conclusions Apply aggregate operations About the reader For readers experienced with spreadsheets and basic Python programming. About the author Boris Paskhaver is a software engineer, Agile consultant, and online educator. His programming courses have been taken by 300,000 students across 190 countries. Table of Contents PART 1 CORE PANDAS 1 Introducing pandas 2 The Series object 3 Series methods 4 The DataFrame object 5 Filtering a DataFrame PART 2 APPLIED PANDAS 6 Working with text data 7 MultiIndex DataFrames 8 Reshaping and pivoting 9 The GroupBy object 10 Merging, joining, and concatenating 11 Working with dates and times 12 Imports and exports 13 Configuring pandas 14 Visualization
Author : Jules S. Damji,Brooke Wenig,Tathagata Das,Denny Lee
Publisher : O'Reilly Media
Page : 400 pages
File Size : 43,7 Mb
Release : 2020-07-16
Category : Computers
ISBN : 9781492050018
Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow
Author : Gabriele Morra
Publisher : Springer
Page : 227 pages
File Size : 49,9 Mb
Release : 2017-08-01
Category : Science
ISBN : 9783319556826
This book addresses students and young researchers who want to learn to use numerical modeling to solve problems in geodynamics. Intended as an easy-to-use and self-learning guide, readers only need a basic background in calculus to approach most of the material. The book difficulty increases very gradually, through four distinct parts. The first is an introduction to the Python techniques necessary to visualize and run vectorial calculations. The second is an overview with several examples on classical Mechanics with examples taken from standard introductory physics books. The third part is a detailed description of how to write Lagrangian, Eulerian and Particles in Cell codes for solving linear and non-linear continuum mechanics problems. Finally the last one address advanced techniques like tree-codes, Boundary Elements, and illustrates several applications to Geodynamics. The entire book is organized around numerous examples in Python, aiming at encouraging the reader to le arn by experimenting and experiencing, not by theory.
Author : Yashavant Kanetkar,Aditya Kanetkar
Publisher : BPB Publications
Page : 381 pages
File Size : 44,5 Mb
Release : 2020-02-11
Category : Computers
ISBN : 9789389845006
Learn Python Quickly, A Programmer-Friendly Guide DESCRIPTION Most ProgrammerÕs learning Python are usually comfortable with some or the other programming language and are not interested in going through the typical learning curve of learning the first programming language. Instead, they are looking for something that can get them off the ground quickly. They are looking for similarities and differences in a feature that they have used in other language(s). This book should help them immediately. It guides you from the fundamentals of using module through the use of advanced object orientation. KEY FEATURES Strengthens the foundations, as detailed explanation of programming language concepts are given in simple manner.Ê Lists down all the important points that you need to know related to various topics in an organized manner. Prepares you for coding related interview and theoretical questions. Provides In depth explanation of complex topics and Questions. Focuses on how to think logically to solve a problem. Follows a systematic approach that will help you to prepare for an interview in short duration of time. Exercises are exceptionally useful to complete the readerÕs understanding of a topic. Ê WHAT WILL YOU LEARN Data types, Control flow instructions, consoleÊ& File Input/Output Strings, list & tuples, List comprehension Sets & Dictionaries, Functions & Lambdas Dictionary Comprehension Modules, classes and objects, Inheritance Operator overloading, Exception handling Iterators & Generators, Decorators, Command-line Parsing Ê WHO THIS BOOK IS FOR Students, Programmers, researchers, and software developers who wish to learn the basics of Python programming language. Ê Table of ContentsÊ 1. Introduction to Python 2. Python BasicsÊÊÊÊ 3. Strings 4. Decision Control Instruction 5. Repetition Control Instruction 6. Console Input/Output 7. Lists 8. Tuples 9. Sets 10. Dictionaries 11. Comprehensions 12. Functions 13. Recursion 14. Functional Programming 15. Modules and Packages 16. Namespaces 17. Classes and Objects 18. Intricacies of Classes and Objects 19. Containership and Inheritance 20. Iterators and Generators 21. Exception Handling 22. File Input/OutputÊ 23. Miscellany 24. Multi-threading 25. Synchronization
