Books & Videos

Table of Contents

Chapter: Getting Started – A Motivating Example

The Course Overview

03m 30s

Getting Started with R

05m 5s

Data Preparation and Data Cleansing

04m 10s

The Basic Concepts of R

05m 46s

Data Frames and Data Manipulation

05m 29s

Chapter: Clustering – A Dating App for Your Data Points

Data Points and Distances in a Multidimensional Vector Space

03m 59s

An Algorithmic Approach to Find Hidden Patterns in Data

06m 24s

A Real-world Life Science Example

04m 28s

Chapter: R Deep Dive, Why Is R Really Cool?

Example – Using a Single Line of Code in R

04m 0s

R Data Types

05m 44s

R Functions and Indexing

04m 14s

S3 Versus S4 – Object-oriented Programming in R

04m 44s

Chapter: Association Rule Mining

Market Basket Analysis

03m 0s

Introduction to Graphs

02m 9s

Different Association Types

05m 27s

The Apriori Algorithm

06m 38s

The Eclat Algorithm

03m 53s

The FP-Growth Algorithm

03m 47s

Chapter: Classification

Mathematical Foundations

06m 0s

The Naive Bayes Classifier

03m 50s

Spam Classification with Naïve Bayes

03m 32s

Support Vector Machines

04m 28s

K-nearest Neighbors

03m 21s

Chapter: Clustering

Hierarchical Clustering

05m 44s

Distribution-based Clustering

06m 54s

Density-based Clustering

03m 11s

Using DBSCAN to Cluster Flowers Based on Spatial Properties

02m 25s

Chapter: Cognitive Computing and Artificial Intelligence in Data Mining

Introduction to Neural Networks and Deep Learning

06m 9s

Using the H2O Deep Learning Framework

02m 28s

Real-time Cloud Based IoT Sensor Data Analysis

06m 17s