Advanced Statistics and Data Mining for Data Science [Video]

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Advanced Statistics and Data Mining for Data Science [Video]

Jesus Salcedo

Your one stop solution to conquering the woes in Statistics, Data Mining, Data Analysis and Data Science

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Video Details

ISBN 139781788830348
Course Length2 hours and 53 minutes

Video Description

Data Science is an ever-evolving field. Data Science includes techniques and theories extracted from statistics, computer science, and machine learning. This video course will be your companion and ensure that you master various data mining and statistical techniques.

The course starts by comparing and contrasting statistics and data mining and then provides an overview of the various types of projects data scientists usually encounter. You will then learn predictive/classification modeling, which is the most common type of data analysis project. As you move forward on this journey, you will be introduced to the three methods (statistical, decision tree, and machine learning) with which you can perform predictive modeling. Finally, you will explore segmentation modeling to learn the art of cluster analysis. Towards the end of the course, you will work with association modeling, which will allow you to perform market basket analysis.

Style and Approach

This application-oriented course takes a practical approach and discusses situations in which you would use each statistical and data mining technique, the assumptions made by the method, how to set up the analysis, and how to interpret the results. No proofs will be derived, but rather the focus will be on the practical aspects of data analysis in answering research questions.

Table of Contents

Data Mining and Statistics
The Course Overview
Comparing and Contrasting Statistics and Data Mining
Comparing and Contrasting IBM SPSS Statistics and IBM SPSS Modeler
Types of Projects
Predictive Modeling
Predictive Modeling: Purpose, Examples, and Types
Characteristics and Examples of Statistical Predictive Models
Linear Regression: Purpose, Formulas, and Demonstration
Linear Regression: Assumptions
Characteristics and Examples of Decision Trees Models
CHAID: Purpose and Theory
CHAID Demonstration
CHAID Interpretation
Characteristics and Examples of Machine Learning Models
Neural Network: Purpose and Theory
Neural Network Demonstration
Comparing Models
Cluster Analysis
Cluster Analysis: Purpose Goals, and Applications
Cluster Analysis: Basics
Cluster Analysis: Models
K-Means Demonstration
K-Means Interpretation
Using Additional Fields to Create a Cluster Profile
Association Modeling
Association Modeling Theory: Examples and Objectives
Association Modeling Theory: Basics and Applications
Demonstration: Apriori Setup and Options
Demonstration: Apriori Rule Interpretation
Demonstration: Apriori with Tabular Data

What You Will Learn

  • Get familiar with advanced statistics and data mining techniques
  • Differentiate between the various types of predictive models
  • Master linear regression
  • Explore the results of a decision tree
  • Work with neural networks
  • Understand when to perform cluster analysis and when to use association modeling

Authors

Table of Contents

Data Mining and Statistics
The Course Overview
Comparing and Contrasting Statistics and Data Mining
Comparing and Contrasting IBM SPSS Statistics and IBM SPSS Modeler
Types of Projects
Predictive Modeling
Predictive Modeling: Purpose, Examples, and Types
Characteristics and Examples of Statistical Predictive Models
Linear Regression: Purpose, Formulas, and Demonstration
Linear Regression: Assumptions
Characteristics and Examples of Decision Trees Models
CHAID: Purpose and Theory
CHAID Demonstration
CHAID Interpretation
Characteristics and Examples of Machine Learning Models
Neural Network: Purpose and Theory
Neural Network Demonstration
Comparing Models
Cluster Analysis
Cluster Analysis: Purpose Goals, and Applications
Cluster Analysis: Basics
Cluster Analysis: Models
K-Means Demonstration
K-Means Interpretation
Using Additional Fields to Create a Cluster Profile
Association Modeling
Association Modeling Theory: Examples and Objectives
Association Modeling Theory: Basics and Applications
Demonstration: Apriori Setup and Options
Demonstration: Apriori Rule Interpretation
Demonstration: Apriori with Tabular Data

Video Details

ISBN 139781788830348
Course Length2 hours and 53 minutes
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