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Practical Business Analytics Using R and Python: Solve Business Problems Using a
US $39.18
ApproximatelyC $54.33
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Like New
A book that looks new but has been read. Cover has no visible wear, and the dust jacket (if applicable) is included for hard covers. No missing or damaged pages, no creases or tears, and no underlining/highlighting of text or writing in the margins. May be very minimal identifying marks on the inside cover. Very minimal wear and tear. See the seller’s listing for full details and description of any imperfections.
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Located in: Somerset, New Jersey, United States
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eBay item number:226667045877
Item specifics
- Condition
- ISBN
- 9781484287538
About this product
Product Identifiers
Publisher
Apress L. P.
ISBN-10
1484287533
ISBN-13
9781484287538
eBay Product ID (ePID)
14057249818
Product Key Features
Number of Pages
Xxv, 706 Pages
Publication Name
Practical Business Analytics Using R and Python : Solve Business Problems Using a Data-Driven Approach
Language
English
Publication Year
2023
Subject
Intelligence (Ai) & Semantics, Economics / General, Databases / General, Programming Languages / Python
Type
Textbook
Subject Area
Computers, Business & Economics
Format
Trade Paperback
Dimensions
Item Weight
48.3 Oz
Item Length
10 in
Item Width
7 in
Additional Product Features
Edition Number
2
Dewey Edition
23
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
658.403
Table Of Content
Section 1: Introduction to Analytics.- Chapter 1: Business Analytics Revolution.- Chapter 2: Foundations of Business Analytics.- Chapter 3: Structured Query Language (SQL) Analytics.- Chapter 4: Business Analytics Process.- Chapter 5: Exploratory Data Analysis (EDA).- Chapter 6: Evaluating Analytics Model Performance.- Section II: Supervised Learning and Predictive Analytics.- Chapter 7: Simple Linear Regressions.- Chapter 8: Multiple Linear Regressions.- Chapter 9: Classification.- Chapter 10: Neural Networks.- Chapter 11: Logistic Regression.- Section III: Time Series Models.- Chapter 12: Time Series - Forecasting.- Section IV: Unsupervised Model and Text Mining.- Chapter 13: Cluster Analysis.- Chapter 14: Relationship Data Mining.- Chapter 15: Mining Text and Text Analytics.- Chapter 16: Big Data and Big Data Analytics.- Section V: Business Analytics Tools.- Chapter 17: R programming for Analytics.- Chapter 18: Python Programming for Analytics.
Synopsis
This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You'll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing. Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. What You Will Learn Master the mathematical foundations required for business analytics Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task Use R and Python to develop descriptive models, predictive models, and optimize models Interpret and recommend actions based on analytical model outcomes Who This Book Is For Software professionals and developers, managers, and executives who want to understand and learn the fundamentals of analytics using R and Python.
LC Classification Number
Q336
Item description from the seller
Seller feedback (4,569)
- b***_ (1055)- Feedback left by buyer.Past 6 monthsVerified purchaseNo Communication Required. 15 Day Transatlantic Shipment. New Item in Excellent Condition as Described. A Satisfying Buy from a Reliable Seller.
- e***e (2539)- Feedback left by buyer.Past 6 monthsVerified purchaseBeautiful book on Georg Jensen, very carefully packed, only down side was the seller did not answer question about condition of book and the description did not provide this information. But the book was in very fine condition and the price was good.
- s***7 (751)- Feedback left by buyer.Past 6 monthsVerified purchaseGreat to deal with, quick to respond and shipped quickly. Item received in great condition as described on the listing. Packaged neatly without sacrificing the value of the item.
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