This Note for Elements of Data Processing is used for revision purposes. It contains all lecture+tutorial topics from week 1 to week 12. Topics include: Data wrangling, Data format, XML/JSON, data pre-processing and data cleaning, Outliers, Recommender systems, Visualisation, Agglomerative, Correlations, Classification and regression techniques ( entropy, Decision Tree etc), record (data) linkage problem, Bloom filter, motivation for blockchain technology, 3 party protocol for privacy, k-anonymity and l-diversity, ethical considerations, big data summary and many more! The notes is quite compact, with few spaces. It covers all examinable materials including lectures and workshops. I used this note to get 92% in final exam. There are 12 pages with 5000+ words of detailed summary and key points to study for. Spending a week on it to get Easy H1 :)


Semester 1, 2018

12 pages

5,308 words



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UniMelb, Parkville

Member since

March 2019

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