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Free Online Book: Mining of Massive Datasets

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The book, like the course, is designed at the undergraduate computer science level with no formal prerequisites. To support deeper explorations, most of the chapters are supplemented with further reading references.


NSF Graduate Research Fellow engineering solutions to big data challenges

#artificialintelligence

For the past six years, first as an undergraduate and now as a doctoral student, Logan Mathesen has used industrial engineering to find solutions to big data problems. His hard work and dedication are paying off, as Mathesen was recently selected as a National Science Foundation Graduate Research Fellow. Mathesen arrived at Arizona State University with the intention of earning bachelor's and master's degrees in industrial engineering through ASU's 4 1 program. However, his strong work ethic and genuine interest in the field prompted his professors to encourage him to apply for the doctoral program directly from the undergraduate program. Logan Matheson was selected as a recipient of the 2018 National Science Foundation Graduate Research Fellowship.


The History of Big Data Processing in 5 Critical Papers

@machinelearnbot

Hadoop, inspired by papers from Google engineers, handled massive amounts of data and processed them in a distributed way, optimizing processing time because it processed where the data was stored minimizing data movements and traffic on the network, using it for coordination. With Hadoop a massive dataset is sharded and replicated to multiples machines in the cluster, when a processing request comes in the processing occurs on the machines with the data in local storage whenever is possible, this data locality feature is a good improvement for clusters using low speed networks. Hadoop was designed for batch processing, to efficiently calculate for example the PageRank of each website on the web, executing a query on a massive dataset and then waiting for the response and continue, this offline or batch processing was a huge improvement but it was fitted for certain type of jobs.


The Watson Effect

#artificialintelligence

After receiving her diploma, recent UT PGE graduate Katy Hanson went to work side-by-side the world's most recognized technology platform. In 2011 IBM's Artificial Intelligence (AI) platform, Watson, went up against the all-time most winning JEOPARDY! Within a few categories Watson's depth and breadth of knowledge surpassed the human brain providing Watson with the win. At that moment, Watson demonstrated to the world the powerful role AI will play in the 21st century. Watson hung up his game-show career, but has been incredibly busy over the past five years gaining vast amounts of insights on many fields, including oil and gas.


Big Data Realization: We are in transition phase

@machinelearnbot

Recently found a post by Ali Syed on topic; "Europeans unconvinced by big data in general". This study was conducted for the Vodafone Institute for Society and Communications by Kantar-owned market researchers TNS Infratest. It analyses over 8,000 individuals across eight European countries and offers valuable insight into people's perceptions of big data and analytics Still there are people or groups don't believe that we are living in the age of Big Data. Other way round we can say they think Big Data is just a hype created by technology people. To me the concept of Big Data is not new.