Pradipsinh C. Profile

5.0

(6 reviews)

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$10 USD / hour

ahmedabad,

india

$10 USD / hour

It's currently 1:31 PM here

Joined July 23, 2014

0 Recommendations

Pradipsinh C.

@pradipsinhchavda

5.0

(6 reviews)

3.7

100%

$10 USD / hour

ahmedabad,

india

$10 USD / hour

100%

Jobs Completed

100%

On Budget

100%

On Time

17%

Repeat Hire Rate

Hadoop,Mapreduce,Java,Spring,Hibernate,MongoDB,AWS

I am java developer.I have hands on experience in advance java technology like spring, hibernate.I have also explored Apache hadoop ,amazon cloud EC2, Machine learning, setting up cluster on EC2, Big data analysis.

See all Java Developers in India

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Reviews

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Showing 1 - 5 out of 6 reviews

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5.0

$35.00 USD

Project for pradipsinhchavda -- 2

very professional in work.

Java

Machine Learning (ML)

Hadoop

Map Reduce

+1 more

Akhil J.

@ubfapps

•

8 years ago

5.0

$89.00 USD

He is too good

Closed User

@mouryay

•

8 years ago

5.0

$401.00 USD

A java program running on Amazon Web Services ....Hadoop for experienced developers

the BEST guy in the world

Java

Cesar Z.

@wq23451

•

8 years ago

5.0

$80.00 USD

java logic modifications

I like pradip's style of straight code with few classes and no abstractions

Java

Machine Learning (ML)

Data Mining

Map Reduce

+1 more

Alex R.

@afterhourstech

•

9 years ago

5.0

$35.00 USD

more work for pradipsinhchavda

complicated code works fine

Java

Machine Learning (ML)

Data Mining

Map Reduce

+1 more

Alex R.

@afterhourstech

•

9 years ago

Education

M.Tech(Computer Science & Engineering)

Gujarat University,

India

2013 - 2015

(2 years)

Publications

Web user’s Browsing Behavior Prediction by Implementing SVM in MapReduce using Cloud Based Hadoop

IEEE

This research work introduces the parallel Support Vector Machines for web page prediction.The performance of the proposed approach is evaluated in amazon cloud EC2 using cloud based Hadoop.

A Survey of Model Used for Web User’s Browsing Behavior Prediction

Computer Engineering and Intelligent Systems

Various models such as fuzzy interference models, support vector machines (SVMs), artificial neural networks (ANNs), association rule mining (ARM), k-nearest neighbor(kNN) Markov model, Kth order Markov model, all- Kth Markov model and modified Markov model were proposed to handle Web page prediction problem.