Data Science

Most influential research papers every data scientist should read!

This is a list of some of the most influential papers in the history of Data Science. We’ve compiled these papers based on recommendations by big data enthusiasts in various social media channels. In case, we’ve missed out any important paper, let us know.
The PageRank Citation Ranking: Bringing Order to the Web
MapReduce: Simplified Data Processing on Large Clusters
The Google File System
Amazon’s Dynamo
Bigtable: A Distributed Storage System for Structured Data
A Few Useful Things to Know about Machine Learning
Random Forests
A Relational Model of Data for Large Shared Data Banks
Map-Reduce for Machine Learning on Multicore
Pasting Small Votes for Classification in Large Databases and On-Line
Recommendations Item-to-Item Collaborative Filtering
Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank
Spanner: Google’s Globally-Distributed Database
Megastore: Providing Scalable, Highly Available Storage for Interactive Services
F1: A Distributed SQL Database That Scales
APACHE DRILL: Interactive Ad-Hoc Analysis at Scale
A New Approach to Linear Filtering and Prediction Problems
Top 10 algorithms on Data mining

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