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Big Data Analytics : Analyzing SPARK performance

I am looking for an expert who can help me in finalizing the base paper and preparing an implementation plan. My goal is characterizing & analyzing the performance of open source analytic engine along with Investigating anomaly detection using optimized ML approaches in input data set. Examining different sensor data sets, replacing incorrect readings, help in decision making.

I need help in preparing implementation plan.

Habilidades: Grande Volume de Dados, Computação em nuvem, Hadoop, Map Reduce, Spark

Ver mais: extract data big files, good data division set

Acerca do Empregador:
( 10 comentários ) Delhi and Chennai, India

ID do Projeto: #11767143

12 freelancers estão ofertando em média $234 para este trabalho

anandsharmainfy

Keenly interested for this project

$200 USD in 5 dias
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cheapgetcode

I can do it.When u need?

$136 USD in 4 dias
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gemini67

Dear Sir, I have done 12 projects in using MATLAB . I have a long experience of working for research work for last many years and I have a team in my office to assist me. regards

$250 USD in 30 dias
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pallavrj

In 15 days, I will go through your requirement and will come up with the best possible proposal or the overall document that you are looking for.

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eversonjuniior

A proposal has not yet been provided

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pradeepred

I have 9 years of exeperience in IT industry with more than 2 years of experience in hadoop technologies like Hive,Pig,Sqoop,Map Reduce and Spark

$155 USD in 3 dias
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iitravindra785

Experience of delivering 3 hadoop project end to end . In your case we need to check the problem statements and choose the best hadoop stack to solve the problem . Bench marking of these tools specific to your problem Mais

$222 USD in 18 dias
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ankratna

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BigdatAnalytix

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$277 USD in 21 dias
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bigdatanetworks

We are a group of 4 members everyone are professional to handle bigdata projects. we delivered 3 projects from past 2 months greatest thing is there is no data leakage in the production environment, more over we are ha Mais

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