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Introduction to Computation and Programming Using Python, Third Edition : With Application to Computational Modeling and Understanding Data by John V. Guttag (2021, Trade Paperback)
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- Buy It NowIntroduction to Computation and Programming Using Python, Third Edition: With
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About this product
Product Identifiers
PublisherMIT Press
ISBN-100262542366
ISBN-139780262542364
eBay Product ID (ePID)14050023815
Product Key Features
Number of Pages496 Pages
Publication NameIntroduction to Computation and Programming Using Python, Third Edition : With Application to Computational Modeling and Understanding Data
LanguageEnglish
Publication Year2021
SubjectProgramming Languages / General, Computer Science, General, Programming Languages / Python
TypeTextbook
AuthorJohn V. Guttag
Subject AreaMathematics, Computers
FormatTrade Paperback
Dimensions
Item Height1.2 in
Item Weight36.1 Oz
Item Length9 in
Item Width7.1 in
Additional Product Features
Intended AudienceTrade
LCCN2020-036760
Dewey Edition23
IllustratedYes
Dewey Decimal005.133
Table Of Content1 GETTING STARTED 2 INTRODUCTION TO PYTHON 3 SOME SIMPLE NUMERICAL PROGRAMS 4 FUNCTIONS, SCOPING, AND ABSTRACTION 5 STRUCTURED TYPES and MUTABILITY 6 Recursion and Global variables 7 Modules and Files 8 TESTING AND DEBUGGING 9 EXCEPTIONS AND ASSERTIONS . 10 CLASSES AND OBJECT-ORIENTED PROGRAMMING 11 A SIMPLISTIC INTRODUCTION TO ALGORITHMIC COMPLEXITY 12 SOME SIMPLE ALGORITHMS AND DATA STRUCTURES . 13 PLOTTING AND MORE ABOUT CLASSES 14 KNAPSACK AND GRAPH OPTIMIZATION PROBLEMS 15 DYNAMIC PROGRAMMING 16 RANDOM WALKS AND MORE ABOUT DATA VISUALIZATION 17 STOCHASTIC PROGRAMS, PROBABILITY, AND DISTRIBUTIONS 18 MONTE CARLO SIMULATION 19 SAMPLING AND CONFIDENCE . 20 UNDERSTANDING EXPERIMENTAL DATA 21 RANDOMIZED TRIALS AND HYPOTHESIS CHECKING . 22 LIES, DAMNED LIES, AND STATISTICS 23 EXPLORING DATA WITH PANDAS 24 A QUICK LOOK AT MACHINE LEARNING 25 CLUSTERING 26 CLASSIFICATION METHODS PYTHON 3.8 QUICK REFERENCE INDEX
SynopsisBased on an MIT massive open online course (MOOC), this book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. This third edition expands the initial explanatory material, making it a gentler introduction to programming for the beginner, with more programming examples and many more "finger exercises." A new chapter shows how to use the pandas package for analyzing time series data. All the code has been rewritten to make it stylistically consistent with the PEP 8 standards. In addition to covering traditional topics, the book focuses on a wide range of topics not found in most introductory texts, including information visualization, simulations to model randomness, computational techniques to understand data, statistical techniques that inform (and misinform), and optimization problems and dynamic programming. The book also includes a Python 3 quick reference guide. Book jacket., The new edition of an introduction to the art of computational problem solving using Python. This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data as well as substantial material on machine learning. All of the code in the book and an errata sheet are available on the book's web page on the MIT Press website.
LC Classification NumberQA76.73.P98G88 2021
