The dsci_553's intro from gxx-s

dsci_553's Introduction

2020 Spring USC DSCI_553 (Foundations and Applications of Data Mining) Homeworks Respority

Description

Data mining is a foundational piece of the data analytics skill set. At a high level, it allows the analyst to discover patterns in data, and transform it into a usable product. The course will teach data mining algorithms for analyzing very large data sets. It will have an applied focus, in that it is meant for preparing students to utilize topics in data mining to solve real world problems

Homeworks

These following code are my homework source code.

No.	Main Application	Programming	Tags	Score
1	Data Exploration	Python	`MapReduce` `Spark` `Pyspark`	8.0 (python) + 0.0 (scala) / 8.0 + 0.8
2	Find Frequent Itemsets	Python	`PCY` `Apriori` `SON`	8.0 (python) + 0.0 (scala) / 8.0 + 0.8
3	Recommendation Systems	Python	`Collaborative Filtering` `MinHash` `LSH`	8.0 (python) + 0.0 (scala) / 8.0 + 0.8
4	Graph Network Algorithm	Python	`Betweenness` `Communities Detection` `Girvan-Newman Algorithm`	6.5 (python) + 0.0 (scala) / 8.0 + 0.8
5	Clustering Algorithm	Python	`K-Means` `Bradley-Fayyad-Reina (BFR) Algorithm` `NMI`	8.0 (python) + 0.0 (scala) / 8.0 + 0.8
6	Streaming Mining	Python	`Bloom Filter` `Flajolet-Martin Algorithm` `Twitter Streaming` `Reservoir Sampling`	8.0 (python) + 0.0 (scala) / 8.0 + 0.8
-	Hybrid Recommendation System	Code	`User Based Collaborative Filtering` `Baseline` `Switching` `Cascade` `User Graph`	RMSE: 1.18

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