Download Ebook Introduction to Computation and Programming Using Python: With Application to Understanding Data (The MIT Press)
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Introduction to Computation and Programming Using Python: With Application to Understanding Data (The MIT Press)
Download Ebook Introduction to Computation and Programming Using Python: With Application to Understanding Data (The MIT Press)
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The new edition of an introductory text that teaches students the art of computational problem solving, covering topics ranging from simple algorithms to information visualization.
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 PyLab. 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. The book is based on an MIT course (which became the most popular course offered through MIT's OpenCourseWare) and was developed for use not only in a conventional classroom but in in a massive open online course (MOOC). This new edition has been updated for Python 3, reorganized to make it easier to use for courses that cover only a subset of the material, and offers additional material including five new chapters.
Students are introduced to Python and the basics of programming in the context of such computational concepts and techniques as exhaustive enumeration, bisection search, and efficient approximation algorithms. Although it covers such traditional topics as computational complexity and simple algorithms, 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, and statistical techniques that inform (and misinform) as well as two related but relatively advanced topics: optimization problems and dynamic programming. This edition offers expanded material on statistics and machine learning and new chapters on Frequentist and Bayesian statistics.
Product details
Series: The MIT Press
Paperback: 472 pages
Publisher: The MIT Press; second edition edition (August 12, 2016)
Language: English
ISBN-10: 0262529629
ISBN-13: 978-0262529624
Product Dimensions:
7 x 0.8 x 9 inches
Shipping Weight: 1.6 pounds (View shipping rates and policies)
Average Customer Review:
4.6 out of 5 stars
32 customer reviews
Amazon Best Sellers Rank:
#78,123 in Books (See Top 100 in Books)
If you're taking MITx 6.00.1x on edX, you NEED this book. This book has a lot of clarifications and examples that will make your progress on the course so much easier. Also, there are free editions of this book available elsewhere, but they don't cover Python 3, and this book does. Well worth the money!
I chose this book for teaching a small intro CS class in Python (3), after reviewing a lot of other books. So many are focused on all the details of the language, but I wanted a book that taught more of the big ideas of computer science/programming. Like: exhaustive enumeration is an amazingly powerful tool in 2016 where our processors go way faster than our programmers go. And bisection search. There's other good, practical outlook in the book. Go read the table of contents. I wish the introduction of OOP were a little easier for beginners. I enjoy Guttag's footnotes and musings.
This is a great book that covers a lot of ground on the field of computer science. Don't expect it to be a step by step guide of how to program in the Python language, or how to use its multiple libraries. Instead this books uses Python to teach you about computation and how to think and solve problems like a computer scientist.Sintaxis, semantics, algorithms and computational complexity are some of the topics you can expect to see in this book, and even though, at some point I had to spent quite a bit of time rereading to grasp some of the concepts, if you have the patience and time, is well worth it!Finger exercises (coding exercises) really give you a chance to put the knowledge you acquire to good use
A very good intro book that not only teaches you the codes/syntax but also methodologies of computing. I bought it for MIT's intro to Python course on EdX, as this is the recommended textbook. The course and the book are both great!
This book is simply amazing. Its purpose is more computer and data science than learning the python language. It is an extensive introduction which dives into stochastic models and inferential statistics. It is really rare to find these topics covered in a book meant for beginners. And you won't believe it but it is fun to read!
This book is a supplement for 6.001x and 6.002x which are introductory computer science courses offered by MIT on edX.org. It is very well written and an absolute must-read if taking the courses.
This is a great book about computer science, but it's a pity that this book (now second edition with a lot of courses and students used it) doesn't follow Python coding convention. If you want to study Python, get an another book, if you are an experienced Python and want to sharpen your computer science knowledge, get this book.
Superb content, as one might expect from MIT. An excellent companion to the MITx: 6.00.n.x series (thus far two) MOOCs. I'll hold onto this one versus selling as used, as is my typical MO after finishing with coursework.
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