Blog Archives

Data Hacking with RDSTK 3

February 16, 2017
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Data Hacking with RDSTK 3

RDSTK is a very versatile package. It includes functions to help you convert IP address to geo locations and derive statistics from them. It also allows you to input a body of text and convert it into sentiments. This is a continuation from the last exercise RDSTK 2 We are going to use the function Related exercise sets:Data Hacking...

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Data Hacking with RDSTK 2

February 11, 2017
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Data Hacking with RDSTK 2

RDSTK is a very versatile package. It includes functions to help you convert IP address to geo locations and derive statistics from them. It also allows you to input a body of text and convert it into sentiments. This is a continuation from the last exercise RDSTK 1 This package provides an R interface to Related exercise sets:Data Hacking...

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Data Hacking with RDSTK (part 1)

January 31, 2017
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Data Hacking with RDSTK (part 1)

RDSTK is a very versatile package. It includes functions to help you convert IP address to geo locations and derive statistics from them. It also allows you to input a body of text and convert it into sentiments. This package provides an R interface to Pete Warden’s Data Science Toolkit. See www.datasciencetoolkit.org for more information. No related exercise sets.

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Let’s get started with dplyr

January 12, 2017
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Let’s get started with dplyr

The dplyr package by Hadley Wickham is a very useful package that provides “A Grammar of Data Manipulation”. It aims to simplify common data manipulation tasks, and provides “verbs”, i.e. functions that correspond to the most common data manipulation tasks. Have fun playing with dplyr in the exercises below! Answers to the exercises are available

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Intermediate Tree 2

January 5, 2017
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Intermediate Tree 2

This is a continuation of the intermediate decision tree exercise. Answers to the exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page. Exercise 1 use the predict() command to make predictions on the

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Intermediate Tree 1

December 29, 2016
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Intermediate Tree 1

If you followed through the Basic Decision Tree exercise, this should be useful for you. This is like a continuation but we add so much more. We are working with a bigger and badder datasets. We will be also using techniques we learned from model evaluation and work with ROC, accuracy and other metrics. Answers

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Model Evaluation 2

December 22, 2016
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Model Evaluation 2

We are committed to bringing you 100% authentic exercise sets. We even try to include as different datasets as possible to give you an understanding of different problems. No more classifying Titanic dataset. R has tons of datasets in its library. This is to encourage you to try as many datasets as possible. We will

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Basic Tree 2 Exercises

December 15, 2016
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Basic Tree 2 Exercises

This is a continuation of the exercise Basic Tree 1 Answers to the exercises are available here. If you obtained a different (correct) answer than those listed on the solutions page, please feel free to post your answer as a comment on that page. Exercise 1 load the tree library. If it is not installed

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Basic Tree 1 Exercises

December 9, 2016
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Basic Tree 1 Exercises

Using the knowledge you acquired in the previous exercises on sampling and selecting(here), we will now go through an entire data analysis process. You will be using what you know as crutches to solve the problems. Don’t worry. It might look intimidating but follow the sequence and you will see that modeling a decision tree

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Select and Query Exercise

December 6, 2016
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Select and Query Exercise

In this exercise we cover the basics on selecting and extracting data using queries. We add a few other materials into it. This should prepare you for the next exercise: Basic Decision Tree. The purpose of this is to give you the 20 percent of the tools to get 80 percent of work done. You

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