Search Constraints
Number of results to display per page
Results for:
Python
Remove constraint Python
Keywords
Textbooks
Remove constraint Keywords: Textbooks
Language
English
Remove constraint Language: English
« Previous |
1 - 10 of 14
|
Next »
Search Results
-
e-book
How to Think Like a Computer Scientist: Learning with Pythonis an introduction to programming using Python.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
-
e-book
The book is based on “First semester in Numerical Analysis with Julia”, written by Giray Ökten. The contents of the original book are retained, while all the algorithms are implemented in Python (Version 3.8.0). Python is an open source (under OSI), interpreted, general-purpose programming language that has a large number of users around the world. Python is ranked the third in August 2020 by the TIOBE programming community index, a measure of popularity of programming languages, and is the top-ranked interpreted language. We hope this book will better serve readers who are interested in a first course in Numerical Analysis, but are more familiar with Python for the implementation of the algorithms. The first chapter of the book has a self-contained tutorial for Python, including how to set up the computer environment. Anaconda, the open-source individual edition, is recommended for an easy installation of Python and effortless management of Python packages, and the Jupyter environment, a web-based interactive development environment for Python as well as many other programming languages, was used throughout the book and is recommended to the readers for easy code development, graph visualization and reproducibility.
- Subjects:
- Computing
- Keywords:
- Numerical analysis Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
-
e-book
A perfect introduction to the exploding field of Data Science for the curious, first-time student. The author brings his trademark conversational tone to the important pillars of the discipline: exploratory data analysis, choices for structuring data, causality, machine learning principles, and introductory Python programming using open-source Jupyter Notebooks. This engaging read will allow any dedicated learner to build the skills necessary to contribute to the Data Science revolution, regardless of background.
- Subjects:
- Computing
- Keywords:
- Data mining Computer science Artificial intelligence Textbooks
- Resource Type:
- e-book
-
e-book
This book will teach you how to make graphical computer games in the Python programming language using the Pygame library.This book assumes you know a little bit about Python or programming in general. If you don’t know how to program, you can learn by downloading the free book "Invent Your Own Computer Games with Python" from http://inventwithpython.com. Or you can jump right into this book and mostly pick it up along the way. This book is for the intermediate programmer who has learned what variables and loops are, but now wants to know, "What do actual game programs look like?" There was a long gap after I first learned programming but didn’t really know how to use that skill to make something cool. It’s my hope that the games in this book will give you enough ideas about how programs work to provide a foundation to implement your own games.
- Subjects:
- Computing
- Keywords:
- Computer programming Computer games Python (Computer program language) Textbooks Programming languages (Electronic computers)
- Resource Type:
- e-book
-
e-book
This text is a practical guide for linguists, and programmers, who work with data in multilingual computational environments. We introduce the basic concepts needed to understand how writing systems and character encodings function, and how they work together at the intersection between the Unicode Standard and the International Phonetic Alphabet. Although these standards are often met with frustration by users, they nevertheless provide language researchers and programmers with a consistent computational architecture needed to process, publish and analyze lexical data from the world's languages. Thus we bring to light common, but not always transparent, pitfalls which researchers face when working with Unicode and IPA. Having identified and overcome these pitfalls involved in making writing systems and character encodings syntactically and semantically interoperable (to the extent that they can be), we created a suite of open-source Python and R tools to work with languages using orthography profiles that describe author- or document-specific orthographic conventions. In this cookbook we describe a formal specification of orthography profiles and provide recipes using open source tools to show how users can segment text, analyze it, identify errors, and to transform it into different written forms for comparative linguistics research.
- Subjects:
- Language and Languages and Computing
- Keywords:
- Language languages -- Orthography spelling Unicode (Computer character set) Textbooks
- Resource Type:
- e-book
-
e-book
"A Byte of Python" is a free book on programming using the Python language. It serves as a tutorial or guide to the Python language for a beginner audience. If all you know about computers is how to save text files, then this is the book for you.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
-
e-book
This text is designed to introduce and expand upon material related to the C programming language and embedded controllers, and specifically, the Arduino development system and associated Atmel ATmega microcontrollers. It is intended to fit the time constraints of a typical 3 to 4 credit hour course for electrical engineering technology and computer engineering technology programs, although it could also fit the needs of a hardware-oriented course in computer science. As such, the text does not attempt to cover every aspect of the C language, the Arduino system or Atmel AVR microcontrollers. The first section deals with the C language itself. It is assumed that the student is a relative newcomer to the C language but has some experience with another high level language, for example, Python. This means concepts such as conditionals and iteration are already familiar and the student can get up and running fairly quickly. From there, the Arduino development environment is examined. Unlike the myriad Arduino books now available, this text does not simply rely on the Arduino libraries. As convenient as the libraries may be, there are other, sometimes far more efficient, ways of programming the boards. Many of the chapters examine library source code to see “what's under the hood”. This more generic approach means it will be easier for the student to use other processors and development systems instead of being tightly tied to one platform. There is a lab manual for this textbook.
-
e-book
I never seemed to find the perfect data-oriented Python book for my course, so I set out to write just such a book. Luckily at a faculty meeting three weeks before I was about to start my new book from scratch over the holiday break, Dr. Atul Prakash showed me the Think Python book which he had used to teach his Python course that semester. It is a well-written Computer Science text with a focus on short, direct explanations and ease of learning.The overall book structure has been changed to get to doing data analysis problems as quickly as possible and have a series of running examples and exercises about data analysis from the very beginning. Chapters 2–10 are similar to the Think Python book, but there have been major changes. Number-oriented examples and exercises have been replaced with data- oriented exercises. Topics are presented in the order needed to build increasingly sophisticated data analysis solutions. Some topics like try and except are pulled forward and presented as part of the chapter on conditionals. Functions are given very light treatment until they are needed to handle program complexity rather than introduced as an early lesson in abstraction. Nearly all user-defined functions have been removed from the example code and exercises outside of Chapter 4. The word “recursion”1 does not appear in the book at all. In chapters 1 and 11–16, all of the material is brand new, focusing on real-world uses and simple examples of Python for data analysis including regular expressions for searching and parsing, automating tasks on your computer, retrieving data across the network, scraping web pages for data, object-oriented programming, using web services, parsing XML and JSON data, creating and using databases using Structured Query Language, and visualizing data. The ultimate goal of all of these changes is a shift from a Computer Science to an Informatics focus is to only include topics into a first technology class that can be useful even if one chooses not to become a professional programmer.
- Subjects:
- Computing
- Keywords:
- Computer programming Programming languages (Electronic computers) Textbooks Python (Computer program language)
- Resource Type:
- e-book
-
e-book
Think DSP is an introduction to Digital Signal Processing in Python. The premise of this book (and the other books in the Think X series) is that if you know how to program, you can use that skill to learn other things. The author is writing this book because he thinks the conventional approach to digital signal processing is backward: most books (and the classes that use them) present the material bottom-up, starting with mathematical abstractions like phasors.
- Subjects:
- Electrical Engineering and Computing
- Keywords:
- Signal processing -- Digital techniques -- Data processing Python (Computer program language) Textbooks
- Resource Type:
- e-book
-
e-book
This book is about complexity science, data structures and algorithms, intermediate programming in Python, and the philosophy of science: Data structures and algorithms: A data structure is a collection that contains data elements organized in a way that supports particular operations. For example, a dictionary organizes key-value pairs in a way that provides fast mapping from keys to values, but mapping from values to keys is generally slower. An algorithm is a mechanical process for performing a computation. Designing efficient programs often involves the co-evolution of data structures and the algorithms that use them. For example, the first few chapters are about graphs, a data structure that is a good implementation of a graph---nested dictionaries---and several graph algorithms that use this data structure. Python programming: This book picks up where Think Python leaves off. I assume that you have read that book or have equivalent knowledge of Python. As always, I will try to emphasize fundmental ideas that apply to programming in many languages, but along the way you will learn some useful features that are specific to Python. Computational modeling: A model is a simplified description of a system that is useful for simulation or analysis. Computational models are designed to take advantage of cheap, fast computation. Philosophy of science: The models and results in this book raise a number of questions relevant to the philosophy of science, including the nature of scientific laws, theory choice, realism and instrumentalism, holism and reductionism, and Bayesian epistemology. This book focuses on discrete models, which include graphs, cellular automata, and agent-based models. They are often characterized by structure, rules and transitions rather than by equations. They tend to be more abstract than continuous models; in some cases there is no direct correspondence between the model and a physical system. Complexity science is an interdisciplinary field---at the intersection of mathematics, computer science and physics---that focuses on these kinds of models. That's what this book is about.
- Subjects:
- Computing
- Keywords:
- Computational complexity Python (Computer program language) Textbooks
- Resource Type:
- e-book