hafizshoaib adlı kullanıcının profil görüntüsü
@hafizshoaib
Pakistan bayrağı Abbottabad, Pakistan
11 Haziran 2013 den beri üye
0 Tavsiyeler

hafizshoaib

Çevrimiçi Çevrimdışı
My research has spanned from general machine learning and data mining to privacy preserving data Science, semi-supervised learning, active learning, Statistics, Probability and Probability Distributions, Stochastic Process and knowledge management. Most of my work has focused on developing and using machine learning & data mining approaches to solve large-scale problems in Predicting Insurance Claims. Secondly I can work on Spatial data , satellite image processing, GISc data using ENVI, ERDAS Imagine, ER Mapper, ArcView, Arc/Info, ArcGIS and Matlab. Other Research Interests are Machine Learning, Deep Learning, Tensor flow and Bayesian Optimization Remote sensing of environment and natural resources GIS, spatial data analysis, geostatistics Environmental Science
$10 USD/hr
1 değerlendirme
0.3
  • 100%Tamamlanmış İşler
  • 100%Bütçe Dahilinde
  • 100%Zamanında
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Portföy

Son Değerlendirmeler

Tecrübe

SS Statistics (BS-17)

Aug 2015

Teaching Statistics

BI Analyst

Mar 2013 - May 2013 (2 months)

Our specialization in Data Management and Business Consulting helps us in delivering valuable solutions to our clients, enabling them in making informed decisions in limited amount of time. We are capable of delivering results faster with significantly less risk and initial investment. Our key service offerings are: usiness Intelligence Analytics Warehousing Science Analytics Learning Quality Assurance

Data Scientist

Dec 2012 - Feb 2013 (2 months)

Working on Medical Lien Management, California, USA projects, performing data analysis on medical insurance settlements; is making exploratory and predictive models for insurance claims and settlements, performing data pre-processing and transformations, Supervised and Unsupervised learning and data mining, Stochastic patterns of the data, Monte Carlo Simulations, manifold techniques for non-linear data, regression, time-series, classification and cluster analysis using various tools.

Eğitim

Masters in Statistics

2010 - 2012 (2 years)

Bachelors in Science

2006 - 2008 (2 years)

Intermediate

2004 - 2006 (2 years)

Matric

2002 - 2004 (2 years)

Remote Sensing and Geographical Information Science

2014 - 2016 (2 years)

Yayınlar

Data Mining in Insurance Claims(DMICS) Two-way mining for extreme values

In insurance claims extreme values are inevitable and cannot be discarded for predictive model building. Moreover, settling insurance claims involves many objections, human sentiments and unseen factors which are hard to be estimated. This simple fact presents the greatest challenge to analysts working on such problems. This paper presents an optimal approach to minimize the effects of this problem on predictive analysis. The data in question includes insurance settlement cases.

Comparison of Maximum Likelihood Classification Before and After Applying Weierstrass Transform

The aim of this paper is to use Maximum Likelihood (ML) Classification on multispectral data by means of qualitative and quantitative approaches. Maximum Likelihood is a supervised classification algorithm which is based on the Classical Bayes theorem. It makes use of a discriminant function to assign pixel to the class with the highest likelihood.

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