Eleonora28
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Big Data Summary
The document provides a summary for the course of Big Data, containing the seven lectures covered, more precisely: Lecture 1: Introduction + Parallel Computing Lecture 2: Map-Reduce and the New Software Stack Lecture 3: Map-Reduce (continued) and Spark Lecture 4: Mining Data Streams (part 1) Lecture 5: Mining Data Streams (part 2) Lecture 6: Frequent Itemset Mining for Big Data Lecture 7: Course Recap
- Summary
- • 86 pages •
The document provides a summary for the course of Big Data, containing the seven lectures covered, more precisely: Lecture 1: Introduction + Parallel Computing Lecture 2: Map-Reduce and the New Software Stack Lecture 3: Map-Reduce (continued) and Spark Lecture 4: Mining Data Streams (part 1) Lecture 5: Mining Data Streams (part 2) Lecture 6: Frequent Itemset Mining for Big Data Lecture 7: Course Recap
Data Mining for Business & Governance summary
This document contains a summary of the 7 lectures for the course of Data Mining for Business & Governance. The summary also contains the links for each practical session and the answers to every formative quiz.
- Summary
- • 105 pages •
This document contains a summary of the 7 lectures for the course of Data Mining for Business & Governance. The summary also contains the links for each practical session and the answers to every formative quiz.