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Big Data Engineering
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EPISODES
Summary and Setup
1. Syllabus
2. Introduction
3. MapReduce Programming Paradigm
4. Spark Computing Environment
5. Data Parallel Computing with Spark
6. Page Rank
7. Locality Sensitive Hashing
8. Frequent Itemsets
9. Clustering
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10. Recommendation Systems
11. Distributed Machine Learning with Spark
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Recommendation Systems
Last updated on 2024-07-26 |
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Overview
Questions
How does Linux come to be?
Objectives
Explain the historical development of Linux
Recommendation Systems
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