must read
data analysis
+2

Contingency Analysis using R

In this tutorial, you'll learn with the help of an example how "Contingency Analysis" or "Chi-square test of independence" works and also how efficiently we can perform it using R.
must read
data analysis
+2
40
40
data manipulation
+2

Diving Deep with Imbalanced Data

Learn the techniques to deal with an imbalanced dataset.
17
17
must read
data analysis
+1

Social Network Analysis in Python

Networks today are part of our everyday life. Let's learn how to visualize and understand a social network in Python using Networks.
must read
data analysis
+1
56
56
importing & cleaning data
+1

Using Regular Expressions to Clean Strings

This tutorial takes course material from DataCamp's Cleaning Data in Python course and allows you to clean strings using regular expressions.
importing & cleaning data
+1
6
6
must read
python
+2

Demystifying Crucial Statistics in Python

Learn about the basic statistics required for Data Science and Machine Learning in Python.
50
50
r programming
+3

Factor Levels in R

This tutorial takes course material from DataCamp's free Intro to R course and allows you to practice Factors.
14
14
r programming
+3

Creating a List in R

Practice Lists in R by using course material from DataCamp's Intro to R course.
8
8
business
+1

Introduction to Customer Segmentation in Python

In this tutorial, you're going to learn how to implement customer segmentation using RFM(Recency, Frequency, Monetary) analysis from scratch in Python.
38
38
must read
r programming
+1

For Loops in R

Practice For Loops in R by using course material from DataCamp's Intermediate R for Finance course.
must read
r programming
+1
13
13
data visualization
+3

Data Visualisation with Tableau

In this tutorial, you will learn how to analyze and display data using Tableau and make better, more data-driven decisions.
72
72
machine learning
+1

TPOT in Python

In this tutorial, you will learn how to use a very unique library in python, tpot . The reason why this library is unique is that it automates the entire Machine Learning pipeline and provides you with the best performing machine learning model.
48
48
r programming

Debug With debugr

In this tutorial, you will learn about debugging in R and Rstudio using the debugr package.
6
6
pandas
+1

Joining DataFrames in Pandas

In this tutorial, you’ll learn various ways in which multiple DataFrames could be merged in python using Pandas library.
58
58
python
+2

Using Python BeautifulSoup to scrape DataCamp Tutorials & Analyze

In this tutorial, we are going to scrape the tutorials section of the DataCamp website and try to get some insights.
47
47
data visualization
+1

Introduction to t-SNE

In this tutorial, you’ll learn about the recently discovered Dimensionality Reduction technique known as t-Distributed Stochastic Neighbor Embedding (t-SNE).
66
66