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Python Data

Location:
Hyderabad, Telangana, India
Salary:
2 lacs /vannum
Posted:
July 28, 2020

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Resume:

RESUME

Email : adewjr@r.postjobfree.com

Mobile : 970*******

LinkedIn : https://www.linkedin.com/in/nelson-raj-

GitHub :https://github.com/nelsonbunnys/nelson

To work in a challenging atmosphere by exhibiting my skills with at most sincerity and dedicated smart work for the growth of esteemed organization along with mine.

Operating Systems

Windows 10.

Programming Languages

Python.

Knowledge In Technology

Data Analysis with Python

Data Visualization with Python

Machine Learning with Python(Linear Regression,Logistic Regression,KNN, k Means Clustering, Decision Tree, Random Forest)

Deep Learning knowledge in tensorflow and keras.

Ms word

Ms Excel

Tools

spyder

Jupyter Notebook

1.ABC Bank Dataset:

The Objective is to predict the amount of credit cards issue by the help of historical

Data.

*. The data which is given is done by using the exploratory data analysis,this process which it mainly helps us to understand the data an used visualization technique to find out the values

*. Used Data Wrangling techniques to find out about the missing values and replace them by creating dummy variables .

* Splitted the data into 70:30 partitions and validated the model

* Summarized the model result and presented to the client

2.Iris Dataset.

Iris dataset is the most widely used dataset for the machine learning model which has 3 species (iris setosa,iris virgininca,iris \versicolor),the data consists of 4 features which consists of Sepal length, Sepalwidth,Petallength,Petalwidth.

3.Wine Quality Dataset.

This is one of the widely used dataset which is used to determine the Dependency of wine quality on the other variables and in wine quality predictions the quality is based on sensory tests this methods were widely used by the industries to promote their products.

4.Object detection: (Vehicle/Person/Object detection).

Object detection is probably the most profound aspect of computer vision due the number practical use cases,Object detection refers to the capability of computer and software systems to locate objects in an image/scene and identify each object. Object detection has been widely used for face detection, vehicle detection, pedestrian counting, web images, security systems and driverless cars.

Achievements

Data Analytics Consulting Virtual Internship From KPMG With Association Of InsideSherpa(June 8,2020)

Deloitte Technology Consulting Virtual Internship (2020) - (Approximately 6 hours) Participated in the open access Deloitte Virtual Internship on InsideSherpa Modules Completed

● Technology, Strategy & Innovation

● Optimization & Delivery

● Cloud Engineering

Accenture discovery programme with the association of Insidesherpa(June 23,2020)

Has completed practical task modules in:

Set Project Priorities Choose your language

Assemble a plan Prioritization & Impact Assessment

User Journey Redesign

Outcomes Analysis Fix the errors

Examination

School/ College

Board/ University

Year of Passing

Percentage

B.sc(MicroBiology)

Noble Degree And Pg College

(Hydeabad)

Osmania University

2018

63.3%

Inter

Scholars Junior College

(Wanaparthy)

Inter Board

(Ap)

2014

70.4%

SSC

Krishnaveni Talent High School

(Wanaparthy)

State Board of Education, AP

2012

83%

PowerBi

Tableau

Data Science

Python for DataScience

Google Analytics for Beginners

DSAR (DataScience Architecture)

AWS attended certificate form AWS

Introduction to internet Of Things

Introduction to Data Analytics

Sex : Male

Date of Birth : 05/08/1997

Marital Status : Single

Nationality : Indian

Languages Known : English,Telugu.

Permanent Address : 28-37/1,Harijanward,Wanaparthy District, pincode - 509103.

Temporary Address : 3-11-244/1, Sri Shankar Colony, LB Nagar,Hyderabad.

DECLARATION:

I hereby declare that the above written particulars are true to the best of my knowledge and believe.

Place: Hyderabad

Date: Sappaku Nelson Raj.

Objective:

Technical Skills:

Projects:

Educational Details

Certificates

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