The document outlines an Edureka training program on data science and predictive analytics, detailing the definition of predictive analytics, its stages, and relevant programming languages like R, Python, and MATLAB. It emphasizes the use of historical data and machine learning to predict future outcomes, with a specific use case involving breast cancer diagnosis. The document also mentions sports analytics and data warehousing as part of the broader context of data science applications.

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Agenda
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What Is Predictive
Analytics?
Stages of Predictive
Analytics
Predictive Analytics
Using R
Hands - On
Predictive Analytics
Use Case

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What Is Predictive Analytics?

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What Is Predictive Analytics?
Predictive analytics is the process of using historical data, machine learning, and artificial intelligence
to predict what will happen in the future.
Historical Data Algorithm
New Data
Model
Predictions

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Stages of Predictive Analytics

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Stages In Predictive Analytics
Define Problem
Statement
Data Collection
Data Cleaning
Data Analysis
Build Predictive
Model
Validate Model
Deployment

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Languages For Predictive Analytics
Python
MATLAB
Java

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Predictive Analytics Using R

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Features Of R
Simple and easy
to learn
Programming &
Statistical language
Data
manipulation
In-built functions for
Data Analysis
8000+ packages
Data visualization
Massive community
support

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Predictive Analytics Use Case

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Sports Analytics
Sports Analytics includes the use of data related to sports such as players’ statistics, weather conditions,
information from expert scouts, etc. and build predictive models around it to make informed decisions.

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Demo

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Predictive Analytics Using R
Dataset Description: The University of California, Irvine (UCI) data set of breast cancer cases which is used to
build a predictive model that classifies a tumour as either malignant or benign based on certain feature variables.
Problem Statement: Implement Predictive Analysis using R to diagnose whether or not a person has breast
cancer, based on past medical data.
Predictive Analysis
Benign Malignant

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Predictive Analytics - Logic
Predictive Analysis
Import Data
Data Cleaning Train Model Improve Efficiency
Test ModelBuild Model

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WebDriver vs. IDE vs. RC
➢ Data Warehouse is like a relational database designed for analytical needs.
➢ It functions on the basis of OLAP (Online Analytical Processing).
➢ It is a central location where consolidated data from multiple locations (databases) are stored.