Feature Exploration, Visualization, and Predictive Modeling with R and Azure ML

In this talk, we will cover an overview of solving a simple predictive analytics problem. We will use R for feature exploration and visualization and build a predictive model using Azure ML.

We will be using the Titanic data set for our exercise. You will see the end-to-end process of building a predictive model. We will start by eyeballing the data set, hypothesizing what features would be useful, and exploring and visualizing features. Eventually, we will build predictive models. We will first be using R and then we will use Azure Machine Learning Studio to show how Azure ML speeds up experimentation.

Table of Contents:
0:00 Introduction
8:09 Box plots
14:29 Histograms and density plots
24:30 Scatterplots
36:20 Reading raw training data
55:50 Class distribution
1:12:58 Density plot
1:17:49 Titanic data

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[arsalan]

a good quality camera would have got my job done in much easier way