Python, Machine Learning,Data visualization,Hadoop, Statistics, Regre

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Aravind C R

Mobile No: +91-948*******

Email: **************@*****.***

OBJECTIVE

Seeking to work in a dynamic environment and contribute towards the goals of the organization using my technical knowledge and skills, in a mutually beneficial way. TECHNICAL SKILLS

Operating System : Ubuntu, Windows.

Languages : C, Core Java, Python.

IDE : PyCharm, Eclipse.

Statistics : Distributions, Hypothesis Testing, Regression. Machine Learning : Regression: Simple, Multiple Linear Regression. Classification: Logistic Regression, k-NN, SVM, Naïve Bayes, Decision Tree & Random Forest.

Clustering: K-Means, Hierarchical.

Others : NumPy, Pandas, Matplotlib, Sklearn, Hadoop, Beautiful Soup. ACADEMIC PROJECTS

Project 1:

Title : Simulation of Self-Driving Car using Convolutional Neural Network. Duration : Jan 2019 – Till date

Team Size : 2

Technology : Python, Keras, Tensorflow, SciKit-learn. Description : The goal of this project was to simulate a self-driving car using concepts from machine learning such as Convolutional Neural Network. In this project, we used neural network to clone car driving behavior. The model used was Nvidia end-to-end model. Testing of the model was done by letting the car drive autonomously on the same track on which training data was collected. Project 2:

Title : Clustering of textual data.

Duration : Aug 2018 - Nov 2018

Team Size : 2

Technology : Python, NumPy, Sklearn, Pandas, Word Cloud. Description : The main objective is to cluster the given data and represent the top representative words among each cluster. Clustering was done with the help of K-means and TF_IDF Algorithms. Top representative words were visualized with the help of word cloud. 2

Project 3:

Title : Mango Classification using CNN.

Duration : March 2018 - June 2018

Team Size : 4

Technology : Python, NumPy, Sklearn, Pandas.

Description : This project is being done as a part of 8nd semester BE. The main objective is to classify

mangoes based on certain attributes like size, color, shape etc. Recognition of image was done with the help Inception V3 model. Layers of CNN layers Input layer, Hidden layer, output layer. Gradient descendent algorithm is used for prediction of instances in data set. ACADEMIC QUALIFICATION

Year QUALIFICATION COLLEGE/UNIVERSITY UNIVERSITY PERCENTAGE 2018

M.E(Big Data

and Data

Analytics)

School of Information Sciences

Manipal Academy of

Higher Education

(MAHE), Manipal

8.36 GPA

(1st Sem)

2018 B.E(CS)

Bangalore Institute of

Technology (BIT), Bangalore.

Visvesvaraya

Technological University,

Belgaum

57.51 %

2014 PUC

Mahesh PU College,

Mangalore.

Karnataka P.U. Board 81.33 %

2012 SSLC

Poorna Prajna Education

Centre, Chikmagalur.

KSEEB 93.12 %

AREAS OF INTEREST

Machine Learning, Data Analytics, Data Visualization. HOBBIES

Listening to Electronic Dance Music, Football.

PERSONAL DETAILS

Fathers name: Ramesh CK

Sex: Male

Date of Birth: 31st

March, 1996.

Permanent Address: Chikmagaravalli,

Aldur (Po), Chikmagalur(Dist)-577111.

Languages Known: Kannada, English and Hindi.

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DECLARATION

I hereby declare that the information furnished above is true to the best of my knowledge. Place: Manipal

Date: Aravind CR

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