Time-series clustering of jobs performance behaviors using (spark/ Hadoop )
Ngân sách $10-30 USD
I am working on a huge number of timeseries of jobs performance behaviors
the goal of my work is to cluster a large number of jobs performance behaviors saved as timeseries and identifying the optimal number of clustering using K-means and Hierarchical and Dynamic Time Warping and compare between the three techniques using Pyspark
I need someone who has good experience in Pyspark especially the dataframe API to do the following tasks:
1- data preprocessing
2- dimensionality reduction
3- apply clustering algorithm (K-means, Hierarchical and Dynamic Time Warping)
4- identify the optimal number of clustering
5- compare between the three techniques
you need to be familiar with Hadoop ecosystem ,spark, Yarn
10 freelancer đang chào giá trung bình $173 cho công việc này
Hi I am a very experienced statistician, data scientist and academic writer. I have completed several PhD level thesis projects involving advanced statistical analysis of data. I have worked with data from several comp Thêm
do kindly reach out to me over chat and we can get started on the task. Also, if there are additional information you can share with me in a zip file
Hi I meet your requirement and have a good experience with Hadoop and [login to view URL] seens to be a huge projet. Contact me and give me more details. After that we will fix the final price.
Hello!I I am very interested in your post project. I am really looking for this kind of project for a long time in freelancer since i have rich experience on it. I think this project is very suitable for me and i am su Thêm
Hi I have 3 years experience in Big Data eco system. spark hdfs yarn flume kafka HBase . Please reach to discuss further.. Thanks
Hi, this is Clark from Shanghai, China. I have more than two years of spark and scala application development experience. I have worked in paypal, google crop as a full time employee and graduated from chinese top3 uni Thêm
Am a spark expert. I have delivered several talks on the topic and am an active speaker in the spark community. Link to one of my talks is below: [login to view URL] Having wo Thêm
