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عنوان
The beginner's guide to data science

پدید آورنده
/ Robert Ball, Brian Rague

موضوع
Data mining ,Big data,a04,a06

رده

کتابخانه
Library of College of Science University of Tehran

محل استقرار
استان: Tehran ـ شهر: Tehran

Library of College of Science University of Tehran

تماس با کتابخانه : 61112616-66495290-021

INTERNATIONAL STANDARD BOOK NUMBER

Qualification
(eISBN)
(Number (ISBN
9783031078651

NATIONAL BIBLIOGRAPHY NUMBER

Number
E4385

LANGUAGE OF THE ITEM

.Language of Text, Soundtrack etc
انگلیسی

TITLE AND STATEMENT OF RESPONSIBILITY

Title Proper
The beginner's guide to data science
General Material Designation
[electronic resources: book]
First Statement of Responsibility
/ Robert Ball, Brian Rague

.PUBLICATION, DISTRIBUTION, ETC

Place of Publication, Distribution, etc.
Cham, Switzerland
Name of Publisher, Distributor, etc.
: Springer
Date of Publication, Distribution, etc.
, 2022.

PHYSICAL DESCRIPTION

Specific Material Designation and Extent of Item
1 online resource.

CONTENTS NOTE

Text of Note
Chapter. 1. Introduction to Data Science -- Chapter. 2. Data Collection -- Chapter. 3. Data Wrangling -- Chapter. 4. Crash Course on Descriptive Statistics -- Chapter. 5. Inferential Statistics -- Chapter. 6. Metrics -- Chapter. 7. Recommendation Engines -- Chapter. 8. Machine Learning -- Chapter. 9 -- Natural Language Processing (NLP) -- Chapter. 10. Time Series -- Chapter. 11. Final Product
0

SUMMARY OR ABSTRACT

Text of Note
This book discusses the principles and practical applications of data science, addressing key topics including data wrangling, statistics, machine learning, data visualization, natural language processing and time series analysis. Detailed investigations of techniques used in the implementation of recommendation engines and the proper selection of metrics for distance-based analysis are also covered. Utilizing numerous comprehensive code examples, figures, and tables to help clarify and illuminate essential data science topics, the authors provide an extensive treatment and analysis of real-world questions, focusing especially on the task of determining and assessing answers to these questions as expeditiously and precisely as possible. This book addresses the challenges related to uncovering the actionable insights in "big data", leveraging database and data collection tools such as web scraping and text identification. This book is organized as 11 chapters, structured as independent treatments of the following crucial data science topics: Data gathering and acquisition techniques including data creation Managing, transforming, and organizing data to ultimately package the information into an accessible format ready for analysis Fundamentals of descriptive statistics intended to summarize and aggregate data into a few concise but meaningful measurements Inferential statistics that allow us to infer (or generalize) trends about the larger population based only on the sample portion collected and recorded Metrics that measure some quantity such as distance, similarity, or error and which are especially useful when comparing one or more data observations Recommendation engines representing a set of algorithms designed to predict (or recommend) a particular product, service, or other item of interest a user or customer wishes to buy or utilize in some manner Machine learning implementations and associated algorithms, comprising core data science technologies with many practical applications, especially predictive analytics Natural Language Processing, which expedites the parsing and comprehension of written and spoken language in an effective and accurate manner Time series analysis, techniques to examine and generate forecasts about the progress and evolution of data over time Data science provides the methodology and tools to accurately interpret an increasing volume of incoming information in order to discern patterns, evaluate trends, and make the right decisions. The results of data science analysis provide real world answers to real world questions. Professionals working on data science and business intelligence projects as well as advanced-level students and researchers focused on data science, computer science, business and mathematics programs will benefit from this book

TYPE OF ELECTRONIC RESOURCE NOTE

Text of Note
PDF file.

TOPICAL NAME USED AS SUBJECT

Entry Element
Data mining
Entry Element
Big data
a04
a06

PERSONAL NAME - PRIMARY RESPONSIBILITY

Ball, Robert, author.

PERSONAL NAME - ALTERNATIVE RESPONSIBILITY

Rague, Brian

ORIGINATING SOURCE

Country
Iran
Agency
University of Tehran. Library of College of Science

ELECTRONIC LOCATION AND ACCESS

Date and Hour of Consultation and Access
UT_SCI_BL_DB_1004762_0001.pdf

e

BL
278840
1

a
Y

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