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time series anomaly detection

the goal of my work is to identify anomaly jobs runing in cloud using job performance KPIs

I have A huge number of jobs over the cloud and each job where executed on a number of nodes

and each node is monitored by a large number of KPIs

so each job KPI(ex: CPU usage ) represents a time series of all nodes CPU usage used at the time the job was executed

**************** using Pyspark **********************************************

I need someone who has good experience in Pyspark especially the data frame API to do the following tasks:

1- data preprocessing

2- feature selection and extraction

3- apply clustering algorithms

4- identify the optimal number of clustering

5- compare between the three techniques

Skills: Python, Spark, Machine Learning (ML), Apache Hadoop, Linux

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About the Employer:
( 0 reviews ) cairo, Egypt

Project ID: #23408789

13 freelancers are bidding on average $165 for this job

schoudhary1553

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