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Data Science with R: A Step by Step Guide with Visual Illustrations & Examples By: Andrew Oleksy | 7.9M | Ebooks - Math/Science/Tech
Author: Andrew Oleksy
Language: English
Publisher:
Publication Date: November 16, 2018
Description: A Step By Step Guide with Visual Illustrations and Examples
The Data Science field is expected to continue growing rapidly over the next several years and Data Scientist is consistently rated as a top career.Data Science with R gives you the necessary theoretical background to start your Data Science journey and shows you how to apply the R programming language through practical examples in order to extract valuable knowledge from data. Professor Andrew Oleksy guides you through all important concepts of data science including the R programming language, Data Mining, Clustering, Classification and Prediction, Hadoop framework and more.
Table of Contents
Introduction to Data Mining
Data Science
Knowledge Discovery in Databases (KDD)
Model Types
Examples and Counterexamples
Classification of Data Mining methods
Applications
Challenges
The R Programming Language
Basic Concepts, Definitions and Notations
Tool Installation
Introduction to R
Data Types
Basic Tasks
Control Structures
Functions
Scoping Rules
Iterated Functions
Help from the console and Package Installation
Types, Quality and Data Preprocessing
Categories and Types of Variables
Preprocessing processes
dplyr and tidyr packages
Summary Statistics and Visualization
Measures of Position
Measures of Dispersion
Visualization of Qualitative Data
Visualization of Quantitative Data
Classification and Prediction
Classification
Prediction
Overfitting and Regularization
Clustering
Unsupervised Learning
Concept of Cluster
K-means algorithm
Hierarchical Clustering Algorithms
DBSCAN Algorithm
Mining of Frequent Itemsets and Association Rules
Introduction
Theoretical Background
Apriori Algorithm
Frequent Itemsets Types
Positive and Negative Border of Frequent Itemsets
Association Rules Mining
Alternative Methods for Large Itemsets generation
FP-Growth Algorithm
Arules Package
Computational Methods for Big Data Analysis (Hadoop and MapReduce)
Introduction
Advantages of Hadoop's Distributed File System
Hadoop Users
Hadoop Architecture
The Hadoop Cluster Architecture
Hadoop Java API
List Loops & Generic Classes and Methods
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