Introduction To Computation And Programming Using Python

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Introduction To Computation And Programming Using Python

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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2013-08-09

Introduction To Computation And Programming Using Python written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-08-09 with Computers categories.

An introductory text that teaches students the art of computational problem solving, covering topics that range from simple algorithms to information visualization.

Introduction To Computation And Programming Using Python Third Edition

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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2021-01-05

Introduction To Computation And Programming Using Python Third Edition written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-05 with Computers categories.

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.

Introduction To Computation And Programming Using Python Second Edition

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Author : John V. Guttag
language : en
Publisher: MIT Press
Release Date : 2016-08-08

Introduction To Computation And Programming Using Python Second Edition written by John V. Guttag and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-08 with Computers categories.

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.

Introduction To Computation Programming Using Python

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Author : JOHN V. GUTTAG
language : en
Publisher:
Release Date : 2017

Introduction To Computation Programming Using Python written by JOHN V. GUTTAG and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.

Introduction To Computation And Programming Using Python

DOWNLOAD
Author : John V. Guttag
language : en
Publisher:
Release Date :

Introduction To Computation And Programming Using Python written by John V. Guttag and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computer programming categories.

Introduction To Computational Social Science

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Author : Claudio Cioffi-Revilla
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-12-31

Introduction To Computational Social Science written by Claudio Cioffi-Revilla and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-31 with Computers categories.

This reader-friendly textbook is the first work of its kind to provide a unified Introduction to Computational Social Science (CSS). Four distinct methodological approaches are examined in detail, namely automated social information extraction, social network analysis, social complexity theory and social simulation modeling. The coverage of these approaches is supported by a discussion of the historical context, as well as by a list of texts for further reading. Features: highlights the main theories of the CSS paradigm as causal explanatory frameworks that shed new light on the nature of human and social dynamics; explains how to distinguish and analyze the different levels of analysis of social complexity using computational approaches; discusses a number of methodological tools; presents the main classes of entities, objects and relations common to the computational analysis of social complexity; examines the interdisciplinary integration of knowledge in the context of social phenomena.

Introduction To Computing And Programming In Python

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Author : Mark Guzdial
language : en
Publisher: Prentice Hall
Release Date : 2005

Introduction To Computing And Programming In Python written by Mark Guzdial and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.

Guzdial introduces programming as a way of creating and manipulating mediaa context familiar and intriguing to today's readers.Starts readers with actual programming early on. Puts programming in a relevant context (Computing for Communications). Includes implementing Photoshop-like effects, reversing/splicing sounds, creating animations. Acknowledges that readers in this audience care about the Web; introduces HTML and covers writing programs that generate HTML. Uses the Web as a Data Source; shows readers how to read from files, but also how to write programs to directly read Web pages and distill information from there for use in other calculations, other Web pages, etc. (examples include temperature from a weather page, stock prices from a financials page).A comprehensive guide for anyone interested in learning the basics of programming with one of the best web languages, Python.

Deep Learning Models And Its Application An Overview With The Help Of R Software Second In Series Machine Learning

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Author : Editor IJSMI
language : en
Publisher: International Journal of Statistics and Medical Informatics
Release Date : 2019-02-09

Deep Learning Models And Its Application An Overview With The Help Of R Software Second In Series Machine Learning written by Editor IJSMI and has been published by International Journal of Statistics and Medical Informatics this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-02-09 with Computers categories.

Deep Learning Models and its application: An overview with the help of R softwarePrefaceDeep learning models are widely used in different fields due to its capability to handle large and complex datasets and produce the desired results with more accuracy at a greater speed. In Deep learning models, features are selected automatically through the iterative process wherein the model learns the features by going deep into the dataset and selects the features to be modeled. In the traditional models the features of the dataset needs to be specified in advance. The Deep Learning algorithms are derived from Artificial Neural Network concepts and it is a part of broader Machine Learning Models. This book intends to provide an overview of Deep Learning models, its application in the areas of image recognition & classification, sentiment analysis, natural language processing, stock market prediction using R statistical software package, an open source software package. The book also includes an introduction to python software package which is also open source software for the benefit of the users.This books is a second book in series after the author’s first book- Machine Learning: An Overview with the Help of R Software https://www.amazon.com/dp/B07KQSN447EditorInternational Journal of Statistics and Medical Informaticswww.ijsmi.com/book.php

Introduction To Computing And Programming In Python A Multimedia Approach Second Edition

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Author : Barbara Ericson
language : en
Publisher: Prentice Hall
Release Date : 2012

Introduction To Computing And Programming In Python A Multimedia Approach Second Edition written by Barbara Ericson and has been published by Prentice Hall this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.

Generative Ai An Overview

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Author :
language : en
Publisher: Editor IJSMI
Release Date : 2025-06-19

Generative Ai An Overview written by and has been published by Editor IJSMI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-19 with Computers categories.

Generative Artificial Intelligence, an Artificial Intelligence concept which is used to create own data which includes creating text, audio, video, images, programming codes and also advanced data structures such as protein structures. Before the Generative AI, Artificial Intelligence models used Machine learning models to predict pattern and structures. Generative AI models are widely being used in Business, healthcare, education and media sectors. Generative AI helps organizations to be more innovative, cost effective and efficient in their operations. Machine learning, Deep Learning, Large Language Models, transformers forms the basis for creating own data in Generative AI environment. Generative AI or Gen AI uses large data set to frame set of rules which is used in creating of new content. ChatGPT and Microsoft Copilot are one of the examples of the Generative AI tools which helps user to create texts and develop answers to users questions. Both proprietary as well as open source Generative aI models are available now. Large Language Models or foundation models which are training large datasets forms the basis of creating contents in Generative AI. These models do not need to be trained and their trained on their own and this is the major difference between supervised Machine learning models which require labeling for classifying the data. Generative AI model building starts with the data collection and processing of large datasets, then moving to model building, training and pattern learning from those large datasets and then finally rendering and validating different created the different types of contents such as text, audio, video and images. The book also provides overview of Python programming for the readers who are first time learners of Python programming. The contents are adopted from Author’s book on Python programming for Data Scientists