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Bestseller
BestsellerE-Book
Author So, Anthony (Data scientist), author.

Title The the Data Science Workshop : Learn How You Can Build Machine Learning Models and Create Your Own Real-World Data Science Projects, 2nd Edition.

Publication Info. Birmingham : Packt Publishing, Limited, 2020.

Copies

Location Call No. Status
 Rocky Hill - Downloadable Materials  EBSCO Ebook    Downloadable
Rocky Hill cardholders click here to access this title from EBSCO
Edition Second edition.
Description 1 online resource (823 pages)
data file rda
Note Print version record.
Contents Cover -- FM -- Copyright -- Table of Contents -- Preface -- Chapter 1: Introduction to Data Science in Python -- Introduction -- Application of Data Science -- What Is Machine Learning? -- Supervised Learning -- Unsupervised Learning -- Reinforcement Learning -- Overview of Python -- Types of Variable -- Numeric Variables -- Text Variables -- Python List -- Python Dictionary -- Exercise 1.01: Creating a Dictionary That Will Contain Machine Learning Algorithms -- Python for Data Science -- The pandas Package -- DataFrame and Series -- CSV Files -- Excel Spreadsheets -- JSON
Exercise 2.01: Loading and Preparing the Data for Analysis -- The Correlation Coefficient -- Exercise 2.02: Graphical Investigation of Linear Relationships Using Python -- Exercise 2.03: Examining a Possible Log-Linear Relationship Using Python -- The Statsmodels formula API -- Exercise 2.04: Fitting a Simple Linear Regression Model Using the Statsmodels formula API -- Analyzing the Model Summary -- The Model Formula Language -- Intercept Handling -- Activity 2.01: Fitting a Log-Linear Model Using the Statsmodels Formula API -- Multiple Regression Analysis
Exercise 2.05: Fitting a Multiple Linear Regression Model Using the Statsmodels Formula API -- Assumptions of Regression Analysis -- Activity 2.02: Fitting a Multiple Log-Linear Regression Model -- Explaining the Results of Regression Analysis -- Regression Analysis Checks and Balances -- The F-test -- The t-test -- Summary -- Chapter 3: Binary Classification -- Introduction -- Understanding the Business Context -- Business Discovery -- Exercise 3.01: Loading and Exploring the Data from the Dataset -- Testing Business Hypotheses Using Exploratory Data Analysis
Visualization for Exploratory Data Analysis -- Exercise 3.02: Business Hypothesis Testing for Age versus Propensity for a Term Loan -- Intuitions from the Exploratory Analysis -- Activity 3.01: Business Hypothesis Testing to Find Employment Status versus Propensity for Term Deposits -- Feature Engineering -- Business-Driven Feature Engineering -- Exercise 3.03: Feature Engineering -- Exploration of Individual Features -- Exercise 3.04: Feature Engineering -- Creating New Features from Existing Ones -- Data-Driven Feature Engineering -- A Quick Peek at Data Types and a Descriptive Summary
Note Correlation Matrix and Visualization
Summary The Data Science Workshop equips you with the basic skills you need to start working on a variety of data science projects. You'll work through the essential building blocks of a data science project gradually through the book, and then put all the pieces together to consolidate your knowledge and apply your learnings in the real world.
Subject Machine learning.
Electronic data processing.
Statistics -- Data processing.
Python (Computer program language)
Application software -- Development.
Programming & scripting languages: general.
Data capture & analysis.
Information visualization.
Computers -- Data Processing.
Computers -- Programming Languages -- Python.
Application software -- Development. (OCoLC)fst00811707
Electronic data processing. (OCoLC)fst00906956
Machine learning. (OCoLC)fst01004795
Python (Computer program language) (OCoLC)fst01084736
Statistics -- Data processing. (OCoLC)fst01132113
Added Author Joseph, Thomas V.
John, Robert Thas.
Worsley, Andrew.
Asare, Samuel.
Other Form: Print version: So, Anthony. Data Science Workshop : Learn How You Can Build Machine Learning Models and Create Your Own Real-World Data Science Projects, 2nd Edition. Birmingham : Packt Publishing, Limited, ©2020
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