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$30 USD / hour
INDIA的国旗
mathura, india
$30 USD / hour
目前这里是4:39 下午
五月 24, 2012已加入
4 推荐

Shiv K.

@SuiGenSolutions

4.8 (153条评论)
7.3
7.3
91%
91%
$30 USD / hour
INDIA的国旗
mathura, india
$30 USD / hour
98%
工作已完成
96%
在预算内
91%
按时
32%
重复雇用率

Scripting | Web Scraping | Custom Web Development

We are a team of experienced and talented professionals based in India. Our team, led by an enthusiastic management comprising a couple of IITians, has expertise in different domains including Mobile App development, Data Analytics, Web App development, Web Scraping etc. We have experience of over 8 years in the field of web scraping, web analytics and other custom web development solutions. Our expertise - Fields - Scripting, Web scraping, Server Administration, E-Commerce solutions, Custom web development, Data Mining Languages - Shell, Python, C#, Java, Node.js, Php Framework - Wordpress, Magento, Spring, Hibernate, AWS, Heroku, Django We provide quality solutions in timely manner. Hire us and you will feel the difference!

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文件夹

2116061
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2116061
2116009
2113486
1340977
1330220
1330213

评论

变更已保存
展示50+中的1-5条评论
筛选评论规则:
5.0
€220.00 EUR
Very good communication, delivered on time. It was nice working with him!
PHP
Java
Python
Web Scraping
Software Architecture
+1更多
S
Closed User
@SportSnapShare
6 年前
4.8
$510.00 USD
Highly reliable and professional! I will hire again!
Java
Android
Objective C
MySQL
AngularJS
用户头像
的国旗 Everlytics Data Science
@winnow1
6 年前
5.0
$475.00 USD
Easy to work with, made a number of adjustments without any problems. Recommended
PHP
Python
Software Architecture
MySQL
Data Mining
+1更多
用户头像
的国旗 Robert S.
@lutherblissett
6 年前
5.0
$180.00 USD
Great freelancer! Will hire again!
D
的国旗 Daniel D.
@ddokhanian1
6 年前
5.0
$200.00 NZD
Excellent Person to with. Highly Recommended!!! A++
用户头像
的国旗 Md Fahmidur R.
@opu00
6 年前

经验

Director

Suigen Solutions
8月 2012 - 现在
Full stack consultant

CDO - GSP

Cisco Systems, Banglore
7月 2011 - 5月 2012 (10 个月, 1 天)
Full stack Java developer

教育

M. Tech.

Indian Institute of Technology, Roorkee, India 2009 - 2011
(2 年)

资质

CCNA

Cisco Systems
2010

出版物

A Reduce Time Complexity Technique For Finding Frequent Item Sets

ICDM 2009 held at IMT Gaziabad, "Data Management" pp 258-264. , 2009
-

Intrusion Detection System based on Real Time Rule Accession and Honeypot

International Conference on Computer Network Security and Applications, 15-17 July 2011. LNCS Springer
-

Design and implementation of IDS using Snort, Entropy and Alert ranking system

IEEE International Conference on Signal, Communication and Network, Kanyakumari, 21-22 July 2011
-

Local Subspace Based Outlier Detection

IC3 2009, CCIS 40, pp. 149-157, 2009. Springer-Verlag Berlin Heidelberg 2009.
Existing studies in outlier detection mostly focus on detecting outliers in full feature space. But most algorithms tend to break down in highdimensional feature spaces because classes of objects often exist in specific subspace of the original feature space. Therefore, subspace outlier detection has been recently defined. As a novel solution to tackle this problem, we propose here a local subspace based outlier detection technique, which uses different subspaces for different objects. Using this concept we

An Enhanced Density Based Spatial Clustering of Applications with Noise

Advance Computing Conference, 2009. IACC 2009. IEEE International, pp. 1475-1478
DBSCAN is a pioneer density based clustering algorithm. It can find out the clusters of different shapes and sizes from the large amount of data which is containing noise and outliers. But the clusters detected by it contain large amount of density variation within them. It can not handle the local density variation that exists within the cluster. For good clustering a significant density variation may be allowed within the cluster because if we go for homogeneous clustering, a large number of smaller unimp

Entity Ranking and Relationship Queries Using an Extended Graph Model

18 th International Conference on Management of Data (COMAD 2012)
There is a large amount of textual data on the Web and in Wikipedia, where mentions of entities (such as Gandhi) are annotated with a link to the disambiguated entity (such as M. K. Gandhi). Such annotation may have been done manually (as in Wikipedia) or can be done using named entity recognition/disambiguation techniques. Such an annotated corpus allows queries to return entities, instead of documents. Entity ranking queries retrieve entities that are related to keywords in the query and belong to a giv

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