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+Data Science Dojo <br/>
+Copyright (c) 2016 - 2019
+
+---
+
+**Level:** Advanced <br/>
+**Recommended Use:** Regression/Classification Models<br/>
+**Domain:** Business/Web<br/> 
+
+## Online News Popularity Data Set 
+
+### Predict the number of shares in social networks 
+
+
+---
+![](OBDL960.jpg)
+---
+
+This *intermediate* level data set has 39644 rows and 61 columns.
+This dataset summarizes a heterogeneous set of features about articles published by Mashable in a period of two years. 
+This could be used to predict the number of shares of an article in social networks.
+
+This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, and **regression/classification modelling techniques**. 
+It also allows you to practice with large number of features. Feel free to explore the data set with multiple **supervised** and **unsupervised** learning techniques. The Following data dictionary gives more details on this data set:
+
+---
+
+### Data Dictionary 
+
 | Column   Position 	| Atrribute Name                	| Definition                                                                                     	| Data Type    	| Example                                                        	| % Null Ratios 	|
 |-------------------	|-------------------------------	|------------------------------------------------------------------------------------------------	|--------------	|----------------------------------------------------------------	|---------------	|
 | 1                 	| URL                           	| URL Of The Article (Non-Predictive)                                                            	| Qualitative  	| "http://mashable.com/2013/01/07/amazon-instant-video-browser/" 	| 0             	|
@@ -60,4 +89,14 @@
 | 58                	| Title_Sentiment_Polarity      	| Title_Sentiment_Polarity: Title Polarity                                                       	| Quantitative 	| -0.1875                                                        	| 0             	|
 | 59                	| Abs_Title_Subjectivity        	| Abs_Title_Subjectivity: Absolute Subjectivity Level                                            	| Quantitative 	| 0                                                              	| 0             	|
 | 60                	| Abs_Title_Sentiment_Polarity  	| Abs_Title_Sentiment_Polarity: Absolute Polarity Level                                          	| Quantitative 	| 0.1875                                                         	| 0             	|
-| 61                	| Shares                        	| Shares: Number Of Shares                                                                       	| Quantitative 	| 593                                                            	| 0             	|
\ No newline at end of file
+| 61                	| Shares                        	| Shares: Number Of Shares                                                                       	| Quantitative 	| 593                                                            	| 0             	|
+
+---
+
+### Acknowledgement
+
+This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Online News Popularity Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Online+News+Popularity). 
+The UCI page mentions the following publication as the original source of the data set:
+
+*K. Fernandes, P. Vinagre and P. Cortez. A Proactive Intelligent Decision Support System for Predicting the Popularity of Online News. Proceedings of the 17th EPIA 2015 - Portuguese Conference on Artificial Intelligence, September, Coimbra, Portugal*
+