Composing Programs

Composing Programs

An introduction to programming and computer science, this text focuses on methods for abstraction, programming paradigms, and techniques for managing the complexity of large programs, using the Python 3 programming language.

Publication date: 01 Jan 2016

ISBN-10: n/a

ISBN-13: n/a

Paperback: n/a

Views: 18,775

Type: N/A

Publisher: n/a

License: Creative Commons Attribution-ShareAlike 3.0 Unported

Post time: 23 May 2016 12:00:00

Composing Programs

Composing Programs An introduction to programming and computer science, this text focuses on methods for abstraction, programming paradigms, and techniques for managing the complexity of large programs, using the Python 3 programming language.
Tag(s): Introduction to Computer Programming Python
Publication date: 01 Jan 2016
ISBN-10: n/a
ISBN-13: n/a
Paperback: n/a
Views: 18,775
Document Type: N/A
Publisher: n/a
License: Creative Commons Attribution-ShareAlike 3.0 Unported
Post time: 23 May 2016 12:00:00
Summary/Excerpts of (and not a substitute for) the Creative Commons Attribution-ShareAlike 3.0 Unported:
You are free to:

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About the Text:

The text was originally published as lecture notes for CS 61A at UC Berkeley and is based upon the Structure and Interpretation of Computer Programs by Harold Abelson and Gerald Jay Sussman.

Table of Contents:

Building Abstractions with Functions - Building Abstractions with Data - Interpreting Computer Programs - Data Processing




About The Author(s)


John DeNero joined the UC Berkeley EECS faculty in 2014. His research in natural language processing focuses on tasks related to statistical machine translation, such as cross-lingual alignment, translation model estimation, translation inference, lexicon acquisition, and unsupervised grammar induction. Prior to his current position, John spent four years as a senior research scientist at Google working primarily on Google Translate, which serves over 1 billion translation requests each day.

John DeNero

John DeNero joined the UC Berkeley EECS faculty in 2014. His research in natural language processing focuses on tasks related to statistical machine translation, such as cross-lingual alignment, translation model estimation, translation inference, lexicon acquisition, and unsupervised grammar induction. Prior to his current position, John spent four years as a senior research scientist at Google working primarily on Google Translate, which serves over 1 billion translation requests each day.


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