Data Machine

Prathvi Kumari

#*,******* ******* ***********

*th cross Gurappana Palya

Btm 1nd stage near total gaz

Bannergatta road bangalore-560029

Mob: +919*********

E-Mail: mailto:rupeshjems2@*****.********************@*****.***

Objective:

To associate myself with an esteemed organization where I can use my analytical and technical skills to provide value addition to the organization as well my personal growth.

Summary of experience

Possessing 3years of experience in teaching and data analytics and data science experience using Python, R machine language .

Technical Skills:

Technology: Python,R langauage,Machine learning.

Environment : Python 2.7 and 3.2, Rstudio.

Good in Python,R scripting, C,C++,Java,Networking,DBMS.

Familiar in Machine Learning, Data Visualization and Data Analysis.

Familiar with Clustering (K-Mean), Linear Regression and Classification Techniques (Random Forest, KNN), ANN (Artificial Neural Network) and SVM (Support Vector Machine),NLP.

Skilled In Numpy, Pandas, Matplotlib, Sklearn and R-Studio.

Work Experience

Worked as lecturer at “shree devi institute of Technology”,from August 2010 to june 2011.

Worked as Asst Professor at “St Joseph Engineering College”,Vamanjoor from July 2013 to may 2014.

Worked as Asst Lecturer at “NITK Surathkal”,from july 2014 to December 2015.

Received training on Machine Learning from Real time signal technologies.

Performed numeric data analysis using Pandas, Numpy and Matplotlib.

Performed model building and performance measure of machine learning models.

Project Details:

#1 Software Fault Prediction Using CK Metric Suite:-

This project aims to assess the influence of CK metrics, keeping in view of predicting faults for an open-source software product.

Statistical methods such as linear regression and logistic regression are used for classification of faulty classes.

Machine learning algorithms such as artificial neural network (ANN) is applied for prediction of faults.

Performance parameters for statistical analysis are determined based on the confusion matrix.

#2 Vehicular Traffic Data Mining Towards Accident and Congestion Prevention:-

Conducted big data analysis in big traffic accident data sets of 146322 examples.

Found useful insight and patterns from the data and predicted possible accidents in advance.

Mine and analyze large size of accident data to test its robustness and effectiveness.

Selecting the most relevant attributes.

Selection of optimum classification algorithm.

#3 : A web search engine based approach to measure semantic similarity between words.

Duration/Size : 6months

Environment : java(data mining)

Description : offline search engine, which searches for phrase, any words and word pair from the static pages which are downloaded and stored in the system local db. To search for word pair and semantic similarity between word pair it uses pattern extraction and clustering methods from snippets and uses page counts. The semantic similarity measure what the user gets for word pair is in the range[0,1] is used to determine semantic similarity between words. if two given words are highly similar is expected to be closer to 1,if given words are not semantic similar is expected to be closer to 0.

Personal Skills:

.

Dedicated to goal and work.

Excellent communication skills and interpersonal skills.

Ability to deal with complicated problems with my own tactics.

Educational Qualification:

Examination

University/Board

Year of Passing

Percentage

MTech (CSE)

Srinivas Institute of Technology

2013

78.00 %

Bachelor of Engineering

(CSE)

Canara engineering college,

Benjanapadav

2009

72.52 %

12th Board (+2)

(Science Stream)

P.U. Board

2005

73.16 %

10th Board

Karnataka Board

2003

83.04 %

Declaration:

I hereby declare that the above-mentioned information is correct.

Date:

Place: Bangalore

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